About the role
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.
Requirements
- 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.
Benefits
- Competitive salary. - Performance bonus. - Stock options/equity consideration. - Opportunity to work on a global AI trading platform.
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