🎓 B.Tech CSE (Artificial Intelligence) — KIET Group of Institutions (2027)
📊 Aspiring Data Analyst / Data Scientist
📍 India
I build data-driven solutions using analytics, machine learning, and business intelligence to solve real-world business problems.
• B.Tech CSE (AI) student at KIET Group of Institutions
• Interested in Data Analytics, Machine Learning, and Financial Analytics
• Passionate about solving business problems using data-driven insights
• Currently building projects in credit risk modeling and customer analytics
A bank-style credit risk modeling system that predicts borrower Probability of Default (PD) and converts it into a credit score used in loan approval decisions.
• Logistic Regression Probability of Default model
• Feature Engineering & Scorecard Calibration
• Credit Scorecard generation for risk assessment
• IFRS-9 Expected Credit Loss estimation
• Interactive Streamlit risk dashboard
Python • Scikit-Learn • SHAP • Streamlit • Power BI
🔗 Live Demo
https://credit-risk-scorecard.streamlit.app
🔗 Repository
https://github.com/ParasJain03/Credit-Risk-Scorecard
An end-to-end telecom churn analytics project that analyzes historical churn behavior and predicts customers likely to leave using machine learning.
CSV Dataset → SQL Server ETL → Data Cleaning → Power BI Dashboard → Random Forest Model → Churn Prediction
• Built SQL ETL pipeline for telecom customer data
• Developed interactive Power BI dashboards for churn insights
• Performed customer segmentation and churn driver analysis
• Trained Random Forest model (~88% accuracy)
• Identified high-risk churn segments for retention campaigns
Python • SQL Server • Power BI • Pandas • Scikit-Learn
🔗 Repository
https://github.com/ParasJain03/customer-churn-analysis
Python • SQL
Pandas • NumPy
Power BI • Matplotlib • Seaborn
Logistic Regression • Random Forest • Model Evaluation
Git • GitHub • Jupyter Notebook • Google Colab
• Advanced Data Analytics
• Financial Risk Modeling
• Feature Engineering for Machine Learning
• Business Intelligence Dashboards
⭐ If you find my projects interesting, feel free to star the repositories.