ML Phase Prediction – HEAs
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Summary
Developed a machine learning solution to predict the phase of High Entropy Alloys (HEAs).
About
Highly analytical and results-driven Data Scientist with a proven track record in developing and deploying advanced machine learning models and data infrastructure solutions. Expertise spans financial forecasting, risk management, consumer segmentation, and data visualization. Adept at leveraging Python, SQL, and AWS to drive quantifiable business impact, including significant cost reductions and revenue improvements. Committed to applying data-driven insights to solve complex challenges and enhance operational efficiency.
Projects
Diabetes Prediction App
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Summary
Created a Flask-based web application for real-time diabetes screening.
AI Ethics Prototype (Stanford)
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Summary
Contributed to the development of an AI risk mitigation tool.
Work
Piramal Finance
|Data Scientist - Credit Risk
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Summary
Leveraged advanced data science and machine learning techniques to optimize credit risk management, financial forecasting, and collections strategies.
Highlights
Architected and deployed an AWS-based financial forecasting simulator, enhancing provision modeling capabilities and enabling flexible scenario analysis through dynamic input variables.
Developed and deployed an XGBoost model for pre-delinquency prediction, achieving a 20% reduction in call-center pre-delinquency costs.
Implemented a reminder system that optimized allocations for over 100K accounts, leading to a 15% increase in on-time payments.
Engineered a predictive ML model to optimize collection strategies, resulting in a 4% improvement in resolution rates.
Created an ensemble model to identify high-probability resolution cases, which decreased collection costs by 20%.
Established a daily NPA forecasting framework for proactive risk management, empowering data-driven provision budgeting decisions and contributing to a 5% reduction in Gross Non-Performing Assets (GNPA).
Spearheaded the automation of critical dashboards using AWS Glue, ensuring accurate and timely data presentation via Power BI for enhanced business intelligence.
OYO
|Data Science Intern
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Summary
Applied machine learning and data visualization techniques to enhance consumer insights and marketing strategies.
Highlights
Developed a machine learning project for property clustering, optimizing the property selection process through the application of the BIRCH algorithm and hyperparameter tuning.
Designed and implemented interactive dashboards using Google Data Studio and Tableau, delivering actionable insights to PR agencies for informed marketing decisions.
Education
Indian Institute of Technology (B.H.U), Varanasi
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B.Tech
Metallurgical Engineering
Grade: 8.96 CGPA