Quantitative Developer

We are seeking a talented Quantitative Developer to join an established and highly successful systematic Stat-Arb Equities team at a tier-one hedge fund in London. This exciting position will be sat on the trading desk, reporting directly in to the Portfolio Manager, forming part of a highly hands-on mid-frequency systematic stat-arb equities team. You will use advanced techniques to enhance existing frameworks and drive further improvements in algorithmic trading performance. Following several highly successful years, the team is expanding and looking for a technically strong quantitative developer who enjoys working closely with a trading team, seeks greater exposure to trading, and is motivated to help drive the ongoing development and enhancement of trading infrastructure and analytics. You will work in a highly collaborative, research driven environment where quantitative developers are involved across the full quantitative lifecycle, including building research and backtesting tooling, implementing trading strategies, optimisation and continuous performance enhancement. This will be alongside working closely with senior members of the team who provide ongoing mentorship, technical guidance, and exposure to strategic decision-making. Key Responsibilities Design, build, and maintain research and production-grade trading infrastructure for systematic equities strategies. Work closely with the Portfolio Manager and quantitative researchers to implement, optimise, and maintain stat-arb equity strategies. Develop robust, efficient, and scalable Python and R codebases for research, backtesting, and live trading. Contribute to improving data pipelines, analytics frameworks, and monitoring tools within a Linux environment. Support strategy performance analysis, debugging, and ongoing enhancement of live models. Take ownership of code quality, testing, and performance in a fast-moving trading environment. Required Qualifications 2-5 years of experience in a Quantitative Developer, Software Engineer, or similar role. Strong hands-on development experience working in a Linux environment. Advanced skills in Python. Solid experience with R. Strong software engineering fundamentals, including version control, testing, and production-ready code. Excellent problem-solving skills, attention to detail, and the ability to work independently in a high performance team. Preferred Qualifications Familiarity with systematic equities strategies. Experience working closely with PMs or traders in a front-office environment. Experience optimising research workflows, backtesting frameworks, or execution systems. Familiarity with large datasets, time-series analysis, and quantitative performance diagnostics. Background in Computer Science, Engineering, Mathematics, Physics, or another quantitative discipline.