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๐Ÿ“œ Description

  • 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.
  • Deploy research into production trading environments.

๐Ÿ› ๏ธ 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.
  • Machine learning (XGBoost, LightGBM, PyTorch).
  • FIX protocol knowledge.

โœจ Benefits

  • Competitive salary.
  • Performance bonus.
  • Stock options/equity consideration.
  • Opportunity to work on a global AI trading platform.
Full job description

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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