Tyler P.

I build trading infrastructure for systematic traders, small funds, and family offices. My work spans strategy validation, backtesting, execution automation, and production deployment - across options, equities, and derivatives. Note: ONLY CONSIDERING CONTRACTS ABOVE $10k USD This is not investment advice, and I do not promise returns. I build the systems and evidence you need to make your own decisions. Strategy Validation Sprint Where most engagements start. I implement your idea, audit the data and assumptions, model realistic transaction costs and fills, and run out-of-sample checks. You get a clear verdict: what works, what breaks, and what to do next. Validated Idea to Production Code If the strategy survives validation, I convert it into a maintainable Python module or service with configs, tests, and standardized outputs - ready for live deployment or handoff to your team. Production Handoff Scheduling, logging, monitoring, alerts, and deployment so runs are unattended and auditable. I work with IBKR, Schwab, and Alpaca for execution integration once logic is proven. What I Typically Work On Options and volatility strategies - covered calls, spreads, iron condors, volatility carry, hedging overlays, and scenario analysis. Systematic equity frameworks - factor and regime filters, ETF rotation, long/short strategies, and portfolio overlays. Execution infrastructure - automated order management, risk controls, position reconciliation, and real-time monitoring across multiple instruments and venues. Market microstructure - for clients exploring newer execution venues, I've deployed production market-making systems with inventory management, on-chain settlement, and real-time execution at scale. This depth informs how I think about execution quality and fill logic across all systems I build. How I Approach Automation I do not start with live trading. Most engagements succeed by moving through phases: validate the strategy, add a manual execution layer (trade sheets, alerts, monitoring), then automate - but only once the logic is proven and the failure modes are defined. Tech Python · Pandas · NumPy · SciPy · scikit-learn · FastAPI · Pydantic · Docker · AWS · asyncio · IBKR · Alpaca · Schwab · Web3 To Get Started Drop me a note with what you're building - the instrument, the general idea, and your timeframe is enough. I'll scope it and lay out the fastest path forward.