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.

Originally posted on Himalayas