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Quantitative Research Scientist - Systematic Trading

Remote / Online - Candidates ideally in
Greater London, London, Greater London, W1B, England, UK
Listing for: eFinancialCareers
Remote/Work from Home position
Listed on 2026-09-05
Job specializations:
  • Research/Development
    Data Scientist, Research Scientist, Research Analyst
Salary/Wage Range or Industry Benchmark: 120000 - 180000 GBP Yearly GBP 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

We are working with a highly successful systematic investment firm looking to add an exceptional
Quantitative Research Scientist to its research team.

This is a genuinely research-led environment. You will work alongside researchers with doctoral and post-doctoral backgrounds in Mathematics, Computer Science, Physics and related disciplines, developing original quantitative ideas and taking the strongest of them all the way into live production.

The firm is looking for people who combine
deep mathematical ability, first-class research credentials and excellent programming skills . Previous experience in finance is not required.

The role

You will work across the full quantitative research process:

  • Develop new statistical and mathematical approaches to extracting signal from large, noisy datasets
  • Research and test new sources of systematic alpha
  • Work with proprietary datasets and infrastructure processing
    billions of market events each day
  • Turn research ideas into robust production implementations
  • Challenge and peer-review research across the team
  • Investigate unconventional or “off-piste” ideas where there is a credible path to investment value
  • Work closely with other researchers throughout the research, validation and implementation process
  • Researchers are given both the infrastructure and intellectual freedom to pursue difficult problems properly. Strong ideas are expected to move beyond academic exercises and ultimately have an impact on live investment strategies.

    Who we are looking for

    We are particularly interested in candidates with:

  • PhD, or completion of a PhD within the next year , in Mathematics, Statistics, Computer Science, Physics, Electrical Engineering or a closely related quantitative discipline
  • An outstanding academic record from a leading university
  • Evidence of genuine research excellence, ideally including
    high-quality peer-reviewed publications
  • Exceptional mathematical and statistical problem-solving ability
  • Strong programming skills and the ability to turn research into reliable working code
  • Very good
    Python skills and confidence working in a Linux environment
  • The ability to explain complex technical ideas clearly and defend research under peer review
  • Intellectual curiosity, independence and an unusually high standard of attention to detail
  • Candidates should be able to demonstrate exceptional academic or technical achievement beyond simply completing a PhD.

    Particularly valuable

    You will stand out further if you have:

  • StrongC++ skills
  • Experience building performance-sensitive or large-scale research systems
  • Competitive programming, open-source development or substantial technical projects
  • Research involving machine learning, statistics, optimisation, time-series analysis or large datasets
  • Some understanding of financial markets, market microstructure or systematic trading
  • Financial experience is not required. Outstanding researchers coming directly from academia are strongly encouraged to apply.

    What matters most is evidence that you are an exceptional researcher and programmer who enjoys difficult mathematical problems and wants to see research translated into real-world outcomes.

    The opportunity

    You will join a small, highly technical research environment with access to proprietary datasets, sophisticated research infrastructure and state-of-the‑art tooling.

    The firm offers a highly competitive compensation package and the opportunity to join one of the fastest-growing and strongly backed systematic investment businesses in London.

    London-based. Partial remote working may be considered#J-18808-Ljbffr
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