Highly accomplished Data Scientist with 5+ years of experience leveraging advanced analytics and machine learning to drive significant business growth and operational efficiencies. Expertly develops and deploys predictive models, implements robust data quality management, and optimizes workflows, consistently delivering measurable impact such as increasing approval rates by 13% and boosting campaign conversion rates by 20%. Proficient in translating complex data into actionable insights and communicating effectively with stakeholders to enable data-driven decision-making.
New Delhi, Delhi, India
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Summary
As a Data Scientist, led the development and deployment of advanced predictive models and AI solutions, significantly enhancing financial risk assessment and operational efficiency.
Highlights
Engineered and deployed a high-performing Credit Risk Scorecard for Used Car Loans using XGBoost, boosting approval rates by 13% and decreasing Non-Performing Asset (NPA) rates by 2% across a ₹3000 Cr portfolio.
Constructed a Decision Tree Banking Scorecard for Open Market Personal Loans, utilizing structured and unstructured financial data to improve risk assessment, increasing acceptance rates by 3% while reducing the event rate.
Designed and implemented an end-to-end Logistic Regression pipeline, integrating IV/CSI calculations, correlation analysis, and RFE, which accelerated feature selection time by 70%.
Architected and implemented a plug-and-play framework for automated reporting, cutting development time by 90%.
Developed an AI agent to analyze call center recordings and extract customer sentiment, delivering real-time suggestions that enhanced agent performance and customer experience.
Engineered an NLP-powered automation pipeline to extract, parse, and standardize financial statements, reducing manual processing time by 85% and enhancing feature engineering efficiency for the UBL Scorecard.
Kolkata, West Bengal, India
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Summary
As a Data Analyst, optimized large customer datasets and generated insightful Power BI reports to facilitate data-driven decision-making.
Highlights
Optimized over 1 million rows of uncleaned customer data through advanced cleaning and preprocessing, ensuring high-quality input for seamless pipeline integration and model readiness.
Designed and developed insightful, interactive Power BI reports, enabling data-driven decision-making for key stakeholders.
Kolkata, West Bengal, India
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Summary
As an Analyst, conducted in-depth data analysis on digital marketing, transforming complex data into actionable insights that improved campaign performance.
Highlights
Conducted in-depth Exploratory Data Analysis (EDA) on digital marketing data using Python and SQL, identifying 5+ key performance trends that boosted campaign conversion rates by 20%.
Developed and delivered over 15 Advanced Excel reports, translating complex datasets into actionable insights for strategic decision-making.
Published by
Research Gate and Cornell University Archives
Summary
Authored a research paper exploring portfolio optimization techniques, comparing Reinforcement Learning with Hierarchical Risk Parity and Eigen Value Portfolio methodologies.
Python, R, SQL.
Pandas, Numpy, Scikit-learn, PySpark.
Matplotlib, Seaborn, PowerBI, Streamlit.
Azure, Databricks, AWS, Git, Docker, Flowise.
Oracle, Advanced Excel.
Logistic Regression, Boosting (Gradient, XGBoost), NLP, Regression Analysis, Hypothesis Testing, Decision Trees, Random Forest, Bagging, Neural Networks, Deep Learning, GenAI, SVM.
Statistical Analysis, Hypothesis Testing, Data Quality Management, Machine Learning, Data Mining, Predictive Modeling, Data Analysis, Data Visualization, Project Management, Model Evaluation, Exploratory Data Analysis (EDA), Feature Engineering, Correlation Analysis, Recursive Feature Elimination (RFE), IV/CSI Calculations.
