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Pooja Master
About Me
I’m a Quantitative Finance professional with experience across quantitative research, risk modeling, portfolio optimization, and financial engineering. I hold an MS in Quantitative Finance from Northeastern University, where I applied programming and statistical techniques to solve real-world financial challenges. My background spans developing risk models (VaR, PD, LGD, EAD), building trading algorithms, optimizing portfolios, and validating complex financial systems. I’ve implemented and backtested systematic strategies, automated reporting pipelines, and delivered insights across equity, fixed income, crypto, and ESG portfolios using Python, SQL, MATLAB, and Tableau. Key Strengths: • Risk Analytics & Model Validation (Monte Carlo, Stress Testing, Basel/IFRS) • Quant Dev & Backtesting (Python, MATLAB, C++, Financial APIs) • Portfolio Optimization (Markowitz, CAPM, ESG Integration) • Financial Data Engineering (SQL, Tableau, Automation, Reporting) I’ve worked on high-impact projects involving algorithmic trading bots, credit risk frameworks, dynamic pricing models, and AI-driven forecasting. My experience combines technical fluency with investment intuition to deliver data-driven, actionable insights. I’m actively seeking opportunities in Quantitative Research, Quant Dev, Risk Modeling, or Portfolio Analytics across financial services, asset management, hedge funds, or fintech.