Equities Quantitative Researcher

Point One - Hedge Fund Talent; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Point One - Hedge Fund Talent in London is seeking an Equities Quantitative Researcher to join a high-performing investment team. The role focuses on research, development and implementation of systematic equity strategies across global markets.

You will work closely with experienced Portfolio Managers to develop predictive models, test signals and enhance the research platform. A strong mathematical background and Python proficiency are essential for success in this front-office role.

Qualifications

• 2–8 years of experience in quantitative research or related buy-side strategy.
• Strong knowledge of statistics, probability, and modelling.
• Advanced Python programming and handling large datasets.

Responsibilities

• Research and develop quantitative signals and alpha factors across global equity markets.
• Analyse large fundamental, market and alternative datasets to identify investable opportunities.
• Design, test and evaluate systematic strategies using robust methodologies.
• Conduct statistical analysis and backtesting to assess signal effectiveness and portfolio impact.
• Collaborate with Portfolio Managers to generate actionable investment insights.
• Develop and enhance research tools, infrastructure and data pipelines.
• Contribute to portfolio construction, risk management and performance attribution.
• Identify new datasets and ML techniques to improve research outcomes.
• Monitor live strategies and investigate performance drivers.
• Collaborate with researchers, developers and investment professionals to improve the process.

Skills

Python

Quantitative research

Statistical modelling

Data analysis

Machine learning

Big data handling

Education

Advanced degree in Mathematics/Statistics/CS/Engineering

Tools

Pandas

NumPy

Backtesting

SQL

Job description

A leading global multi-strategy hedge fund is seeking an Equities Quantitative Researcher to join a high-performing investment team based in London. This is a front-office role focused on the research, development and implementation of systematic investment strategies across global equity markets, supporting investment decision-making within a highly collaborative platform.

This position offers direct exposure to experienced Portfolio Managers and the opportunity to contribute innovative investment ideas, develop predictive models and identify new sources of alpha. The successful candidate will play a key role in signal research, portfolio construction and the ongoing enhancement of the team's systematic investment process, operating within a fast-paced environment where rigorous analysis and intellectual curiosity are highly valued.

Key Responsibilities

• Research and develop quantitative signals and alpha factors across global equity markets.
• Analyse large fundamental, market and alternative datasets to identify investable opportunities.
• Design, test and evaluate systematic investment strategies using robust research methodologies.
• Conduct statistical analysis and backtesting to assess signal effectiveness and portfolio impact.
• Work closely with Portfolio Managers to generate actionable investment insights and support decision-making.
• Develop and enhance research tools, infrastructure and data pipelines.
• Contribute to portfolio construction, risk management and performance attribution analysis.
• Identify and evaluate new datasets, methodologies and machine learning techniques to improve research outcomes.
• Monitor live strategies and investigate performance drivers across portfolios.
• Collaborate with researchers, developers and investment professionals to improve the overall investment process.

Requirements

• Approx. 2-8 years of experience within quantitative research, systematic equities, statistical arbitrage or a related buy-side investment strategy.
• Strong understanding of statistics, probability, data analysis and quantitative modelling techniques.
• Advanced programming skills in Python and experience working with large datasets.
• Experience developing, testing and evaluating predictive investment signals or quantitative strategies.
• Knowledge of equity market dynamics, factor investing and portfolio construction principles.
• Experience applying machine learning, data science or advanced analytical techniques within a financial context is advantageous.
• Strong analytical and problem-solving skills with excellent attention to detail.
• Ability to thrive in a fast-paced, front-office investment environment and communicate research findings effectively.
• Advanced degree in Mathematics, Statistics, Physics, Computer Science, Engineering, Finance or a related quantitative discipline is preferred.

For more information contact:

Thomas Hennelly – [e-mail]

Graham Murphy – [e-mail]