Quantitative Model Developer – Research Technology - Multi-Strategy Hedge Fund - London - Up to £400k TC

A well-established hedge fund with a strong track record is seeking to expand its Research Technology team. The group supports the in-house research function by developing scalable applications, data infrastructure, and modelling platforms to deliver high-quality insights for investment decision-making.

The Role

As a member of the Research Technology team, you will:

• Develop model code to transform research models into scalable, production-ready applications.
• Maintain and enhance the research modelling platform to support faster testing of new ideas.
• Build scalable data pipelines and integrate data from relevant systems.
• Work with Risk Managers, Portfolio Managers, and the Investment Committee to ensure effective application of research outputs.

Key Responsibilities

• Design, build, and maintain efficient and reliable Python code and infrastructure.
• Develop and maintain the risk modelling, pricing, and analytics suite.
• Partner with business users to deliver new tools, troubleshoot existing solutions, and provide guidance on best practices.
• Explore and implement new approaches to analytics and data handling across multiple asset classes (Equities, Fixed Income, Credit, FX).

Candidate Profile

• Strong programming skills in Python (Pandas, NumPy), with MATLAB experience required.
• Familiarity with other data analysis tools (R, Eviews) is an advantage.
• Experience managing projects from requirements gathering through to testing and release.
• Strong communication, problem-solving, and organisational skills.
• Prior front-office or risk technology experience within a bank, asset manager, or hedge fund is desirable.

Academic Qualifications

• A-Levels at grades A*/A/B (or international equivalent).
• First-class degree in a STEM subject or related field from a Russell Group university (or international equivalent).

Additional Information

• The fund operates across a broad range of complex instruments, including rates, FX, equity derivatives, commodities, and credit.
• The environment is fast-paced and detail-oriented, requiring strong technical skills and adaptability.
• Compensation is competitive, with the potential for performance-related bonuses.