Seeking Quant Developer to Optimize XAUUSD Trading Bot – Reduce Drawdown & Improve Risk Management

I’m looking for an experienced algorithmic trading developer to optimize a gold (XAUUSD) trading bot that operates exclusively during the Sydney session. The current bot has shown strong profitability (+65% return on 100K capital) but suffers from high drawdown (-142%) and inconsistent risk management. Your mission: Refine the strategy to maintain profitability while drastically reducing risk exposure. Key Objectives ✅ Reduce maximum drawdown (Current: -142% → Target: 30%) ✅ Improve Profit Factor (Current: 1.22 → Target: 1.5) ✅ Enhance Win Rate (Current: 46.67% → Target: 55%) ✅ Implement dynamic risk management (ATR-based stop-loss, position sizing) ✅ Optimize for Sydney session volatility (low liquidity, specific price action patterns) ✅ Backtest & validate improvements (5+ years of XAUUSD data, walk-forward testing) Available Data & Tools Full trade history (300+ trades, entry/exit logic, P&L breakdown) Current bot code (Specify language: MQL4/MQL5/Python) Backtest reports (MetaTrader 4/5, TradingView, or custom framework) Initial capital: $100,000 | Current return: +65% Required Skills (Mandatory) ✔ Proven experience in forex/gold algorithmic trading (GitHub portfolio, live results, or client references). ✔ Proficiency in: MQL4/MQL5 (MetaTrader) or Python (Backtrader, Zipline, QuantConnect) Statistical analysis (Sharpe Ratio, Sortino, Max Drawdown, Monte Carlo simulations) Risk management techniques (Kelly Criterion, volatility-based position sizing) Sydney session specifics (low liquidity, Asian market influence on XAUUSD) ✔ Ability to explain changes clearly (technical reports, commented code). ✔ Familiarity with gold (XAUUSD) price drivers (USD strength, geopolitical events, safe-haven flows). Deliverables Comprehensive Audit Report Identify why drawdown is excessively high (e.g., lack of stop-loss, over-leveraging). Detect overfitting/curve-fitting biases in the current strategy. Optimized Trading Logic Revised entry/exit rules tailored for Sydney session. Dynamic risk management (e.g., ATR-based stops, time-based filters). Updated Bot Code Fully commented, ready for live deployment. Compatible with your platform: MT4/MT5/custom. Backtest Comparison Before/after performance metrics (Profit Factor, Win Rate, Drawdown). Walk-forward testing on 2018–2023 XAUUSD data. User Documentation Optimal parameters for different market conditions. Guide on adjusting settings for changing volatility. Apply tot his job