Currently working at JPMorgan Chase as Data Scientist and Applied AI Machine Learning Lead Engineer. Experienced financial professional with a comprehensive cross-asset derivatives and management background in creating quantitative trading strategies for hedge fund and institutional investors, working at preeminent investment banks (Goldman Sachs, Lehman Brothers, and Société Générale). Developed and coded trading, PNL, and portfolio analytic platforms. In these roles, have managed teams of quantitative professionals. Recently, complimented my expertise by completing a MS degree in Data Science (MSDS) concentrating in Machine Learning at Southern Methodist University in December 2018, a national leader in Big Data and Machine Learning higher education. Recent published project, coded in Python: "Improving VIX Futures Forecasts Using Machine Learning Methods" (see Publications section of this website for link). Also have MBA from MIT Sloan; and BSEE and MSEE from Tufts University. AREAS OF EXPERTISE: Mortgage Securities; Data Science; Machine and Deep Learning; Macro Cross-Asset Strategy; Smart Beta and Alpha Strategies; Model and Strategy Backtesting; Global Indices and ETFs; Derivative/Volatility Trades; Equity, Credit & VIX Options; Hybrid/Structured OTC Options; Commodity, FX and Rates.COMPUTER SKILLS: Python, MS SQL, BLP API, R, R-Studio, Matlab, MySQL, MongoDB, SAS, Processing, C++, Slang/SecDb, Visual Basic, OptionMetrics, and some Java
Listed skills include Equity Derivatives, Credit Derivatives, Derivatives, Options, and 49 others.