Forex Quant Backtesting Python Programmer

I’m building out a series of quantitative strategies for the FX market and want a clean, repeat-able way to see how each idea would have fared historically. Everything will be written in Python; feel free to lean on pandas, NumPy, vectorized calculations, or a framework such as Backtrader or Zipline if that speeds development, provided the final code remains transparent and easy for me to extend.

Scope
• Ingest and normalize historical Forex price data (I already have the data files; just need automated loading and preprocessing).
• Code the strategy template so I can drop new rule sets into a single function or class and rerun tests quickly.
• Generate key statistics—CAGR, max drawdown, Sharpe, win/loss, and equity curves—plus simple visualizations.
• Allow walk-forward or out-of-sample testing by date ranges.

Delivery & acceptance
• Well-commented Python scripts or notebooks.
• A short README explaining folder structure, required packages, and how to run a new backtest.
• Sample run demonstrating the framework against one EUR/USD strategy and producing the resulting metrics and chart.

If you’ve tackled quantitative Forex work before and write clean, modular code, this should be straightforward—and we can always expand into live execution logic once the backtester is nailed down.