Oussama M.

Financial Engineer | Quantitative Research, Backtesting & Python

Financial engineers who can also build are rare. Most quant profiles you'll find on Upwork are either researchers who can't ship production code, or developers who don't actually understand the math behind what they're building. I sit at the intersection of both. I take options theory, volatility models, and systematic trading ideas and turn them into pricing engines, backtesting frameworks, and analytics platforms that hold up against real market data under real market conditions. My core focus is derivatives analytics and systematic strategy research. I have spent years working with options Greeks, implied volatility surfaces, GARCH-family volatility models, and event-driven backtesting infrastructure. I do not just prototype, I build things that run. Recent projects that show the kind of work I do: Built a live real-time Greeks and IV-surface dashboard for options analysis. The system computes delta, gamma, vega, and theta in real time, fits the implied volatility smile across strikes and expiries, and flags unusual options flow for further investigation. Backtested a portfolio of SPX options selling strategies with realistic transaction costs, proper fill modeling, and full attribution of win rates, drawdown, and risk-adjusted returns across different market regimes. Reverse-engineered a portfolio of systematic strategies from raw historical trade records, extracting the underlying logic into explicit, testable rules and quantified risk parameters. On the technical side I cover the full stack a serious quant project needs. For options work that means Black-Scholes and binomial pricing, full Greeks computation, IV surface fitting, and smile and skew modeling. For backtesting that means event-driven and vectorized frameworks, walk-forward validation, realistic cost and fill modeling, and detailed performance attribution. For research that means GARCH and stochastic volatility models, factor analysis, time-series econometrics, and return forecasting. For data infrastructure that means market data pipelines, research-ready datasets, and broker and FRED API integrations. Stack: Python with pandas, numpy, scipy, and QuantLib, plus R, Julia, and SQL depending on what the project calls for. I am trilingual in English, French, and Arabic, which means I can work directly with MENA and Francophone institutions without translation overhead or communication friction. If your project needs someone who genuinely understands the financial theory behind the code and not just someone to run scripts, send me a short description of the scope. I reply within a few hours and offer a free 30-minute scoping call for any project over $500.