New Delhi, Delhi, India
→
Summary
Currently leading advanced analytics and machine learning initiatives to develop and deploy predictive models, optimizing financial risk assessment and operational efficiency for a 3000Cr portfolio.
Highlights
Developed and deployed a high-performing Credit Risk Scorecard for Used Car Loans (UCL) using XGBoost, increasing the approval rate by 13% and reducing Non-Performing Assets (NPA) by 2% for a ₹3000Cr portfolio.
Built a Decision Tree Banking Scorecard for Open Market Personal Loans (OMPL), leveraging structured and unstructured financial data to enhance risk assessment, increasing acceptance by 3% while reducing the event rate.
Designed an end-to-end Logistic Regression pipeline, incorporating IV/CSI calculations, correlation analysis, and Recursive Feature Elimination (RFE), which reduced feature selection time by 70%.
Architected a plug-and-play framework for automated reporting, reducing development time by 90% and streamlining data delivery.
Developed an AI agent for analyzing call center recordings, extracting customer sentiment, and providing real-time suggestions to enhance agent performance and customer experience.
Engineered an NLP-powered automation pipeline to extract, parse, and standardize financial statements (PDFs, ZIPs), reducing manual processing time by 85% and improving feature engineering efficiency for the UBL Scorecard.
Kolkata, West Bengal, India
→
Summary
Performed comprehensive data analysis on digital marketing data, identifying key performance trends and delivering actionable insights to improve campaign effectiveness.
Highlights
Conducted in-depth exploratory data analysis (EDA) on digital marketing data using Python and SQL, identifying over 5 key performance trends that increased campaign conversion rates by 20%.
Delivered 15+ advanced Excel reports, transforming complex data into clear, actionable insights for strategic decision-making.
Highly accomplished Data Scientist with 5+ years of experience leveraging advanced analytics and machine learning to drive significant business growth and operational efficiency. Proven expertise in developing and deploying high-performing predictive models, optimizing data quality, and automating workflows to deliver measurable impact. Adept at transforming complex data into actionable insights and communicating strategic recommendations to stakeholders, fostering data-driven decision-making.
Published by
Research Gate and Cornell University Archives
Summary
Authored and published research exploring advanced portfolio optimization techniques using Reinforcement Learning with Hierarchical Risk Parity and Eigen Value Portfolio.
Logistic Regression, Boosting (Gradient, XGBoost), Decision Trees, Random Forest, Bagging, Neural Networks, Deep Learning, SVM, NLP, GenAI, Predictive Modeling, Model Evaluation.
Python, R, SQL, Advanced Excel, Git, Docker, Oracle, Azure, AWS, Databricks, Streamlit, Flowise, PowerBI.
Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, PySpark.
Statistical Analysis, Hypothesis Testing, Regression Analysis, Data Mining, Data Quality Management, Data Analysis, Data Visualization, Project Management.