Projects
A collection of my work and side projects
Featured Projects
Agentic NL2SQL System
Engineered multi-agent architecture that achieves 50.87% execution accuracy on BIRD benchmark while reducing inference cost by 90%. Preserves privacy using locally finetuned SLMs through LoRA & QLoRA that can run on consumer-grade hardware. Accepted at CAI 2026 Conference.
Interpretable Credit Risk Models
Built interpretable credit risk models using Ensemble Models + LIME that achieve 76% accuracy while ensuring regulatory compliance and full model transparency. Published at CADSCOM 2024 & Accepted at AMLDS 2025.
Insurance Predictive Modeling
Developed rare-event classifiers for Travelers Insurance call center staffing needs using zero-inflated regression and advanced feature engineering on highly imbalanced data. Evaluated with Gini index for production model selection.
LLMOps ETL Pipeline
Built end-to-end ETL + LLMOps workflow at Amazon supporting 97 ARS sites across North America. Integrated QuickSight dashboards for real-time monitoring of mission-critical metrics.
Other Projects
Solar Energy Anomaly Detection
Built statistical & ML anomaly detection algorithms for solar energy data that flagged hidden inefficiencies early, reducing energy waste and cutting costs in Amazon fulfillment centers.
2022 World Cup Performance Analytics
Scraped and processed FIFA statistics; built dashboards with radar plots and bar charts analyzing team performance metrics for the 2022 World Cup.
REAL TIME CUSTOMER CHURN PREDICTION
Built a real-time churn prediction platform: trained a Random Forest pipeline, streamed events via Kafka, processed features in Spark, and served predictions through a React dashboard. Why it is Important Customer acquisition costs 5-25x more than retention. By identifying at-risk customers early, businesses can deploy targeted interventions like personalized offers, proactive support, or contract adjustments to reduce churn and protect revenue.