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ParasJain03/README.md

Hi, I'm Paras Jain 👋

Python Machine Learning Power BI SQL

🎓 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.

👨‍💻 About Me

• 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

🚀 Featured Projects

🏦 Credit Risk Scorecard — IFRS-9 PD Model

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.

Key Features

• 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

Tech Stack

Python • Scikit-Learn • SHAP • Streamlit • Power BI

🔗 Live Demo
https://credit-risk-scorecard.streamlit.app

🔗 Repository
https://github.com/ParasJain03/Credit-Risk-Scorecard

📊 Customer Churn Analysis — SQL, Power BI & Machine Learning

An end-to-end telecom churn analytics project that analyzes historical churn behavior and predicts customers likely to leave using machine learning.

Data Pipeline

CSV Dataset → SQL Server ETL → Data Cleaning → Power BI Dashboard → Random Forest Model → Churn Prediction

Key Features

• 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

Tech Stack

Python • SQL Server • Power BI • Pandas • Scikit-Learn

🔗 Repository
https://github.com/ParasJain03/customer-churn-analysis

🛠 Technical Skills

Programming

Python • SQL

Data Analysis

Pandas • NumPy

Data Visualization

Power BI • Matplotlib • Seaborn

Machine Learning

Logistic Regression • Random Forest • Model Evaluation

Tools

Git • GitHub • Jupyter Notebook • Google Colab

📚 Currently Learning

• Advanced Data Analytics
• Financial Risk Modeling
• Feature Engineering for Machine Learning
• Business Intelligence Dashboards

📫 Connect With Me

Email

LinkedIn

Phone

⭐ If you find my projects interesting, feel free to star the repositories.

Pinned Loading

  1. Credit-Risk-Scorecard Credit-Risk-Scorecard Public

    Bank-style Credit Risk Scorecard using Logistic Regression, IFRS-9 Expected Credit Loss, and an Interactive Streamlit Risk Dashboard for loan default prediction.

    Jupyter Notebook 5

  2. customer-churn-analysis customer-churn-analysis Public

    End-to-End Customer Churn Analysis using SQL ETL, Power BI Dashboard, and Machine Learning (Random Forest) for churn prediction.

    Jupyter Notebook 4