Overview
Our client is a leading $25bn multi-strategy hedge fund, recognised globally for its robust infrastructure, deep resources, and long-term commitment to systematic and discretionary investment talent. The firm provides its Portfolio Managers with cutting-edge technology, capital, and operational support, enabling them to focus on generating alpha and scaling their strategies.
Role Overview:
We are seeking a talented Statistical Arbitrage Portfolio Manager to build and run a dedicated stat arb strategy. This is an outstanding opportunity to join a platform that offers meaningful capital allocation, full budget for research and data, and the freedom to hire and manage your own team of researchers, quants, and technologists.
The fund is open-minded to candidates with diverse backgrounds, whether you are a senior researcher ready to step up into a PM role, or an experienced Portfolio Manager seeking a more supportive environment following a challenging year.
Key Responsibilities
- Design, develop, and implement statistical arbitrage strategies across global equities and/or other liquid asset classes.
- Manage risk, capital allocation, and portfolio construction within firm guidelines.
- Build and lead a team of researchers and data scientists to enhance idea generation and execution.
- Collaborate with technologists to optimise data pipelines, infrastructure, and execution.
- Continuously research and integrate new data sources and methods to improve signal quality and returns.
- Operate within a strong risk management framework while maintaining innovation and flexibility in strategy design.
Requirements
- Proven experience in statistical arbitrage (equities, futures, or multi-asset) as a Portfolio Manager, Senior Researcher, or Sub-PM.
- A strong track record of developing and running systematic trading strategies (short- to medium-horizon), with annual pnl returns of $20m or more.
- Advanced quantitative and statistical skills; PhD or MSc in a quantitative discipline (e.g. Mathematics, Statistics, Computer Science, Physics, Engineering) preferred.
- Deep understanding of market microstructure, execution, and transaction cost analysis.
- Proficiency in programming languages such as Python, C++, or Java, and experience with large datasets.
- Entrepreneurial mindset with the ability to build and manage a high-performing team.
- A collaborative, open-minded approach to research and idea sharing.
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