Hitik Panchal

Project Lead for NCMS CM Application (NSE Clearing Management System) for National Stock Exchange of India. Refactored backend code, reducing database load by ~10% and eliminating critical bugs, which improved overall system performance by ~4-5%. Led NCMS CM API design and restructuring, migrating the Java/Spring Boot monolith to an API-based architecture, which increased system efficiency by ~20% and enhancing capacity to handle ~20,000+ trades per minute, aligning with business goals.

Executed production deployments on Linux for NCMS serving 100,000+ end users, maintaining near-zero downtime across all release cycles. • Led Git migration of 10+ legacy NCMS codebases, standardising version control across the team and significantly reducing branch conflicts and manual merge overhead. • Resolved critical SQL and application bugs during UAT and testing phases, reducing defect backlog and accelerating time-to-production for key features.

Built an end-to-end customer churn prediction pipeline (logistic regression + decision tree ensemble, scikit-learn) on 200,000+ subscription records; optimised for AUC score and delivered risk scores surfaced via Tableau dashboards adopted by the marketing team for retention targeting. • Engineered ETL workflows for data cleaning, feature engineering, and model tuning, streamlining the path from raw data to production-ready model inputs.

Current Grade: 1.7 · Focus: Machine Learning, NLP, Large Language Models

CGPA: 9.76 / 10 · Final-year thesis on real-time crowd density estimation using CNN/MCNN (~90% accuracy)