Quantitative Developer

My clients is seeking an experienced Quantitative Developer to design, build, and optimise high-performance trading systems within prediction markets and market-making environments. This role is suited to candidates with a proven track record delivering high Sharpe strategies in HFT or similarly latency-sensitive domains. You will work on end-to-end system development, including signal research, execution infrastructure, and real-time risk management.

The ideal candidate combines strong engineering discipline with a deep understanding of market microstructure, probabilistic modelling, and alpha generation. Key Responsibilities: Develop and maintain low-latency trading systems in Java, Python, or Rust Design and implement predictive models for pricing and execution Optimise market-making strategies across multiple venues Build robust backtesting and simulation frameworks Collaborate closely with researchers and traders to deploy live strategies Continuously improve system performance, reliability, and scalability Requirements: Extensive experience in HFT, market making, or prediction markets Demonstrated ability to generate high Sharpe ratio strategies Strong programming skills in Java, Python, or Rust Deep knowledge of data structures, algorithms, and concurrency Solid understanding of market microstructure and execution dynamics Experience working with large datasets and real-time data pipelines Degree in a quantitative field (Maths, Physics, Computer Science, Engineering) Desirable: Experience with exchange connectivity, FIX protocols, or crypto markets Background in statistical modelling, ML, or probabilistic forecasting Familiarity with Linux systems, networking, and performance tuning Location & Flexibility: Preferably London-based, but open to remote candidates within compatible time zones This is a high-impact role in a fast-moving environment, offering significant autonomy and the opportunity to directly influence trading performance.