Senior Quantitative Developer

The Company Our client is a financial technology (FinTech) company specifically focused on bridging the gap between man and machine when it comes to investing. They are building an AI-driven trading and investing platform covering stocks, futures, forex, and crypto. They develop quantitative strategies, portfolio models, copy trading solutions, and low-latency execution systems. Our client aims to be the world's most trusted AI trading platform where sophisticated market intelligence meets effortless execution, enabling every trader to compete with institutional-level strategies while maintaining full control over their investment decisions. The Role Our client is seeking a Senior Quantitative Developer to design, build, test, and deploy systematic trading strategies. The ideal candidate combines strong software engineering skills with quantitative finance and algorithmic trading experience. Key Responsibilities Develop and maintain quantitative trading strategies. Build backtesting, optimization, and portfolio construction frameworks. Implement walk-forward analysis, Monte Carlo testing, and robustness validation. Work with market data including equities, futures, forex, and crypto. Integrate machine learning models into trading workflows. Collaborate with Java execution and platform engineering teams. Deploy research into production trading environments. Monitor strategy performance and improve risk-adjusted returns. Success Metrics Build 100+ validated strategy candidates annually. Develop production-grade research infrastructure. Improve portfolio Sharpe ratio and reduce drawdowns. Create scalable AI-driven trading models. 5+ years Python development experience. Strong knowledge of Pandas, Polars, NumPy. Experience with VectorBT, Backtrader, or QuantConnect LEAN. Strong statistics and quantitative finance knowledge. Portfolio optimization and risk management experience. Experience with futures, forex, equities, or crypto trading. Knowledge of PostgreSQL, TimescaleDB, and cloud environments. Git, Docker, CI/CD experience. Preferred Skills Machine learning (XGBoost, LightGBM, PyTorch). FIX protocol knowledge. Interactive Brokers, Alpaca, or LMAX integrations. Java or C++ exposure. Experience with institutional trading systems. Competitive salary. Performance bonus. Stock options/equity consideration. Opportunity to work on a global AI trading platform.