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Join a systematic equities research team responsible for discovering, validating and scaling differentiated equity alpha across global markets. You will own end-to-end research workstreams including data selection, feature engineering, modelling, testing and performance evaluation, and see successful ideas deployed with real capital. The role requires strong quantitative and Python skills, experience delivering live equity alpha, and is based on-site in London or New York.
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- £100,000 – £225,000 GBP
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- London, New York City
- Country
- United Kingdom, United States
Currency: £ (GBP)
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Job Details
Quantitative Researcher - Systematic Equities
- £100000 - £225000 per annum
- City of London, London
- Permanent
Quantitative Researcher - Systematic Equities
Location: London or New York
Industry: Hedge Funds
Working Model: On-site
Overview
This position offers the chance to join a systematic equities research function responsible for building and scaling differentiated alpha across global equity markets.
The mandate is pure research: identifying new sources of equity alpha, validating them rigorously, and seeing successful ideas deployed with real capital. Researchers operate end-to-end, with ownership over data selection, signal design, testing, and ongoing performance evaluation.
This is particularly well suited to researchers who already run live signals but want greater influence over the research agenda, cleaner decision-making, and a clearer line of sight between their work and outcomes.
Responsibilities:
- Researching, designing, and validating new systematic equity alpha signals across regions and time horizons
- Owning the full research lifecycle: data exploration, feature engineering, modelling, testing, and performance analysis
- Working closely with other senior researchers to combine signals into robust portfolios
- Contributing to portfolio construction and risk discussions, with clear visibility of live outcomes
- Leveraging an advanced research and execution stack built for speed, scale, and iteration
- Operating in a collaborative environment where good ideas move quickly into production
Experience:
- Strong academic foundation in a quantitative discipline (Mathematics, Physics, Computer Science, Engineering or similar)
- MSc or PhD from a leading university preferred
- Proven experience delivering live equity alpha in a buy-side or systematic trading environment
- Deep understanding of statistics, time-series analysis, and modern machine learning techniques
- Advanced Python skills for research and production-quality code
- Self-directed, intellectually honest, and motivated by research quality over noise
Compensation:
Competitive compensation with meaningful performance participation and full benefits.
McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.
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