Full job description Location: London
A leading global investment firm is seeking a Quantitative Researcher to join its Systematic Equities team. Working closely with a Senior Portfolio Manager, you’ll be responsible for researching and developing alpha-generating strategies using a combination of statistical techniques, machine learning and large-scale data analysis.
This is an opportunity to work in a highly collaborative environment where research is taken from concept through to live implementation and has a direct impact on portfolio performance.
What You’ll Be Doing
*Generate and evaluate new alpha ideas for systematic equity strategies.
*Research, clean and analyse a wide range of structured and alternative datasets.
*Design, test and refine predictive models using statistical and machine learning techniques.
*Build robust research infrastructure and analytical tools in Python.
*Perform rigorous backtesting and validation of trading signals.
*Collaborate closely with the Portfolio Manager throughout the research and investment process.
*Write high-quality, maintainable code and contribute to a shared research framework.
What We’re Looking For
*Master’s or PhD in a quantitative discipline such as Mathematics, Physics, Statistics, Computer Science or Engineering.
*Strong Python programming skills and experience building quantitative research tools.
*Excellent analytical ability with a scientific, hypothesis-driven approach to problem solving.
*Strong communication skills and the ability to work effectively in a collaborative research environment.
Desired Experience
*At least three years’ experience researching systematic equity strategies.
*Proven track record developing and testing equity alpha signals.
*Experience working with intraday equity data and quantitative trading models.
*Familiarity with statistical learning techniques and predictive modelling.
Additional Experience of Interest
*Research involving alternative datasets or fundamental data.
*Statistical arbitrage or market-neutral equity strategies.
*Machine learning applications within quantitative investing.
*Commercial mindset with strong intuition for identifying robust investment opportunities.