Quantitative Developer - Systematic Equities

About the role

Millennium, a global hedge fund, is looking for a Quantitative Developer for its systematic equities team in Dubai. The role leads the design and deployment of the core trading infrastructure for a newly formed quantitative trading pod, working directly with quantitative researchers and the Senior Portfolio Manager to turn research ideas into production-ready strategies. It is a hands-on leadership position owning the technology stack from day one.

Key responsibilities

• Design and maintain the trading system architecture (data ingestion, signal generation, backtesting, execution, risk management) with low latency, high throughput and fault tolerance
• Lead a small team of developers and mentor junior developers and quant developers
• Build research infrastructure such as backtesting frameworks, simulation environments and feature stores
• Translate researcher prototypes (e.g. in Python) into production-grade code, often in C++ or C# for latency-sensitive parts
• Optimize order execution systems and integrate with exchanges or broker APIs
• Implement real-time risk checks, monitoring, logging and alerting
• Oversee data pipelines for market, alternative and internal data, ensuring integrity and low-latency access
• Own deployment pipelines, version control and production support, and ensure compliance and security standards

Required profile

• Bachelor's or Master's degree in Computer Science, Mathematics, Physics, Engineering or a related quantitative field
• 3+ years of hands-on experience building high-performance trading systems, ideally in systematic equities or quant trading
• Experience with large-scale market data, order routing and FIX/DMA, and event-driven real-time systems
• Excellent communication with researchers and traders, initiative and comfort in fast-paced environments

Required skills

• C++ or C# for performance-critical systems; Python for scripting and research integration
• Algorithms, data structures and multithreaded programming
• SQL and modern databases (column stores, time-series)
• Git, unit testing, CI/CD, logging and monitoring