Data Scientist

Automated ingestion and standardization of over 1 million rows/day of Bloomberg and proprietary macro data using Python and SQL, improving data pipeline efficiency by 30%. Developed real-time dashboards tracking $100M+ in portfolio exposure, including live PnL, NAV, VaR, and liquidity risk metrics, directly supporting CIO decision-making. Contributed to internal projects focused on pipeline optimization and automation, leveraging Python, SQL, and AI-driven insights to identify bottlenecks and improvement opportunities. Conducted correlation and regime-based clustering across FX, equities, and rates, informing tactical allocations under various macro scenario.

Delivered market research and strategy decks for $5M+ finance and risk transformation programs across banking and insurance sectors, aligning business goals with regulatory shifts and digital trends. Led stakeholder interviews with 15+ senior executives to capture business requirements, risk pain points, and transformation KPIs. Built Excel-based operational models and interactive Power BI dashboards used by clients to simulate headcount planning, cost allocation, and process performance; improved planning efficiency by 20%. Supported 3 cross-functional project teams in executing data strategy workshops, guiding clients through data maturity assessment, governance frameworks, and system integration planning.