£150,000 - 200,000 GBP

Performance Based Bonus

Onsite WORKING

Location: Central London, Greater London - United Kingdom Type: Permanent

Systematic Equity Statistical Arbitrage Quantitative Researcher

Our client is a leading systematic multi-strategy hedge fund with a strong track record of deploying data-driven investment strategies across global markets. As part of the continued growth of its Systematic Equities platform, the firm is looking to hire an exceptional Quantitative Researcher with experience developing statistical arbitrage strategies.

This is an opportunity to join a high-performing research team with access to world-class infrastructure, extensive datasets, and significant resources to develop, test, and scale alpha-generating strategies across global equity markets.

Responsibilities

• Research, develop, and implement systematic statistical arbitrage strategies across global equity markets.
• Generate and evaluate novel alpha signals using rigorous quantitative research methodologies.
• Design and maintain robust backtesting and simulation frameworks to assess strategy performance.
• Enhance portfolio construction, risk modelling, and execution to improve risk-adjusted returns.
• Apply machine learning and advanced statistical techniques to extract predictive signals from large and alternative datasets.
• Collaborate closely with Portfolio Managers, Quantitative Researchers, and Engineers to take research ideas from conception through to production.

Requirements

• 3+ years of experience researching and developing systematic equity statistical arbitrage strategies within a hedge fund, proprietary trading firm, or quantitative asset manager.
• Demonstrable track record of generating alpha through systematic research.
• MSc or PhD in Mathematics, Statistics, Computer Science, Physics, Engineering, or another highly quantitative discipline from a leading university.
• Strong understanding of statistics, probability, time series analysis, optimisation, and machine learning techniques.
• Excellent programming skills in Python and/or C++, with experience building scalable research tools.
• Experience working with large financial datasets, backtesting frameworks, and quantitative research infrastructure.
• Strong communication skills and the ability to collaborate effectively within a research-driven environment.

Desirable Experience

• Experience working with alternative datasets and feature engineering.
• Familiarity with modern machine learning techniques applied to financial markets.
• Knowledge of portfolio optimisation, transaction cost modelling, and execution research.

What's on Offer

• Opportunity to work alongside some of the industry's leading quantitative researchers and portfolio managers.
• Access to industry-leading technology, datasets, and research infrastructure.
• A highly collaborative, intellectually stimulating research environment.
• Competitive compensation package, including a market-leading bonus structure directly linked to performance.
• Significant scope to contribute to strategy development and research from day one.