I’m a Quantitative and Technology Lead who sits at the intersection of Finance, Risk, Models, AI, Data and Engineering. I’m equally comfortable discussing FRTB capital numbers with risk managers, debugging Monte Carlo code with quants, developing Gen AI (CAG) solutions and Agentic AI workflows, building end to end data lineage tool for Market Risk, or developing full-stack Edtech tool for Generative AI. Over the last several years, I’ve worked on Data Governance and Controls, Calculation of VaR, Expected Shortfall, FRTB SA/IMA, DRC, RRAO, Stress Testing, Counterparty Credit Risk, SACCR, CCAR, Country Risk, Scenario Exposure Analysis for Credit and Market Risk, Stressed RWA Calculation, Model Validation, Model Development and Derivatives Pricing, helping global banks turn complex regulatory, risk and trading requirements into robust, production-ready models and platforms. I was able to contribute and deliver given the trust that my managers have shown over the years involving me in new and cross project initiatives within the organization and allowing me to gain experience of contributing at various stages of project delivery. My problem-solving style is end-to-end: I don’t just build models; I build systems around them. I’ve reviewed and optimized quantitative impact (QIS) engines across asset classes, parallelized and vectorized MC simulations to cut runtimes from hours to minutes, and designed Python-based capital calculators for securitization and structured products. On the data and controls side, I’ve created decomposition and lineage tools that ingest reports, map data flows, apply CDE logic, and generate audit-ready evidence for BCBS 239. In parallel, I’ve been building AI and ML driven solutions from RAG/CAG-based regulatory workbenches, Gen AI assisted Model Validation, Agentic flow for VaR calculation to analytics that help traders and risk managers ask better questions of their data. What ties all of this together is a focus on practical impact and cross-functional execution. I use Python, modern ML, and full-stack development not as buzzwords but as levers to reduce manual effort, improve transparency, and make complex risk concepts usable for the organizations. Whether the challenge is a broken data pipeline, a misbehaving pricing engine, or an ambiguous regulatory requirement, I enjoy breaking the problem down, structuring it, and delivering solutions that scale across teams, regions, and use cases. Nominated for BITS 30 under 30 in 2025 Fast tracked promotions to AVP and Lead Quants Nominated for Best Graduating Student - 2019 (Top 5)