I have built a rules-based options selling strategy and hedging it using Futures for the National Stock Exchange and now need to see hard numbers before taking it live. I’m looking for a Hyderabad-based Python developer who already understands option chains, Greeks, expiry calendars, and margin mechanics, and who can wire the logic into NinjaTrader for a rigorous historical back-test. You will receive the full trade rules and parameter ranges from me. Your task is to: • Code the strategy in clean, modular Python that interfaces smoothly with NinjaTrader. • Pull or import reliable NSE F&O data, then run multi-year back-tests with adjustable date windows. • Produce an easily digestible performance report—equity curve, drawdown, Sharpe, win-loss stats—as well as the raw trade log. • Keep all key variables (lot size, strike filter, stop/target, re-entry rules) in a config area so I can iterate without touching the source. • Comment the code clearly; I’ll be maintaining it after delivery. Acceptance criteria 1. Strategy executes across at least five years of historical data with no runtime errors. 2. Reported P&L and trade counts reconcile with NinjaTrader logs. 3. Parameter changes can be made and re-tested in under two minutes per year of data. Local availability in Hyderabad is preferred so we can sit down once for hand-off and future tweaks, but we can collaborate remotely day-to-day. When you reply, please highlight any prior derivatives work—especially spread or delta-hedged projects—and give me a ballpark timeline for a first working prototype.