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