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.