Quantitative Developer - Trade Systems, Data Platform & Risk - Hedge Fund - London

Attribution Search is partnered with a leading global hedge fund, looking to hire Quantitative Developers across both Trading, and Data Platform & Risk Analytics teams.

These roles offer the opportunity to work in a high-performing, front-office environment, building systems that directly support systematic trading, portfolio analytics, and risk management across multiple asset classes.

Responsibilities:

As a member of the team, you will be involved across the full software development lifecycle, working closely with quants, traders, and risk teams to deliver scalable and high-performance solutions.

Depending on team alignment, responsibilities will include:

• Developing and maintaining Python-based tools supporting systematic trading strategies
• Supporting the full lifecycle of trading systems, from research and backtesting through to production deployment and monitoring
• Building and maintaining data platforms and analytics systems covering P&L, VaR, scenarios, and exposure reporting
• Designing and optimising data ingestion, storage, and access layers for large-scale financial datasets
• Developing low-latency components in C# for performance-critical workflows
• Ensuring production systems are reliable, well-tested, and scalable
• Collaborating closely with stakeholders to translate business requirements into technical solutions

Requirements:

• Degree in Computer Science, Mathematics, Engineering, or a related quantitative field
• 5+ years’ experience in quantitative development, software engineering, or data platform roles
• Strong Python experience in a production environment
• Experience working with data pipelines, analytics systems, or trading platforms
• Exposure to high-performance or low-latency systems (C#, Java, or C++)
• Strong SQL skills and experience working with relational databases
• Familiarity with large-scale data processing and time-series datasets
• Experience with messaging systems (e.g. RabbitMQ, Kafka)
• Exposure to modern tooling such as Docker, Kubernetes, and cloud platforms (AWS)
• Understanding of systematic trading environments or financial products is beneficial
• Strong analytical and problem-solving skills
• Excellent communication and ability to work with cross-functional teams

Candidates with relevant experience are encouraged to apply to find out more.