We are working with a growing multi-manager, multi-strategy digital asset hedge fund to appoint a Quantitative Strategy & Technology Analyst. The firm allocates to external quantitative trading teams across statistical arbitrage, market-making, long/short, trend-following and other systematic strategies.
The opportunity
Working directly with senior management in London, you will combine quantitative analysis, technology development and AI automation to support investment and operational decisions. This is a broad role offering exposure to portfolio construction, manager evaluation and risk management, with scope to take ownership and influence how the business develops.
Key responsibilities
- Portfolio construction: Develop tools to optimise manager and strategy weightings and monitor live versus target allocations.
- Risk analytics: Build dashboards and frameworks to assess exposures, correlations, drawdowns and portfolio risks.
- AI and technology: Develop agents, applications and automated workflows across research, portfolio management and operations.
- Manager evaluation: Improve how the firm sources, screens, evaluates and monitors quantitative trading teams.
- Process improvement: Identify inefficiencies and build practical, scalable solutions.
Candidate profile
Approximately two to five years’ professional experience, ideally supported by a master’s degree in Computer Science, Data Science, Mathematics, Econometrics, Financial Engineering or a related discipline. Candidates returning to industry following relevant postgraduate study or academic research are also welcome.
You will bring
- Strong programming skills, particularly Python, and excellent quantitative capabilities.
- Evidence of building useful tools, analysing complex datasets or automating processes.
- Practical AI experience or a strong interest in applying AI to investment workflows.
- Intellectual curiosity, initiative and an interest in financial markets and systematic trading.
- The ability to work across technical, investment and operational projects within a small team.
Candidates from technology, engineering, academia and other industries are welcome. Technical ability, practical project experience and an appetite to learn matter more than prior financial services experience.
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