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.

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.