Senior Trading Data Analyst / Quantitative Analytics Engineer

We need an experienced Quantitative Trading Data Analyst or Senior Python Engineer to strengthen the analytics core of our trading research platform. This is not a live trading role. The system already has basic data ingestion and backtesting. Your job is to turn it into a reliable, professional-grade research engine that traders can trust. What You’ll Do Build clean data pipelines (Polygon / Databento) with proper handling of corporate actions, rolls, and point-in-time data Create accurate performance analytics (Profit Factor, Expectancy, Sharpe, Max DD, etc.) Add research modules: day-of-week, time-of-day, volatility regimes, slippage modeling Develop comparison tools and clear visualizations (equity curves, drawdowns, heatmaps) Deliver a prioritized improvement roadmap for the development team Required Experience Strong Python with large financial datasets (Pandas/Polars) Real experience with futures or equity market data Deep understanding of backtesting pitfalls (look-ahead bias, survivorship, realistic fills) Proven work building or reviewing quant/research tools Engagement Phase 1: Paid review + written recommendations and roadmap (8–15 hours) Phase 2+: Ongoing implementation work for the right candidate How to Apply Answer these directly: Describe a trading analytics or quant research tool you built or improved. How do you review backtests to find false positives or unrealistic assumptions? How do you handle point-in-time data and look-ahead bias? Are you available for a paid review in the next 7–10 days? Practical market experience is more important than theory.