Quantitative Researcher – Postgraduate

G-Research
City of London
2 months ago
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We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.


From our London HQ, we unite world‑class researchers and engineers in an environment that values deep exploration and methodical execution – because the best ideas take time to evolve. Together we’re building a world‑class platform to amplify our teams’ most powerful ideas.


Join a research team where curiosity meets scale. You’ll investigate foundational questions, uncover market insights and push the boundaries of what’s possible – all with the support of near‑limitless compute and world‑class peers.


Take the next step in your career.


The role

Our researchers use the latest scientific techniques and advanced statistical analysis methods to predict movement in global financial markets.


This requires harnessing massive compute power and using state‑of‑the‑art machine‑learning techniques to find innovative solutions, as textbook methods won’t beat the competition.


This is a pure research role where you will develop and test your ideas with real‑world data in an academic environment.


Machine Learning College


ML College is an established, in‑house learning programme at G‑Research. It’s designed to develop our researchers into fully‑fledged machine‑learning practitioners through a world‑class, custom curriculum.


ML College is exclusive to new and existing Quantitative Researchers at G‑Research, so if you join us in this role you’ll benefit from a learning experience tailored to accelerate your knowledge and expertise in machine‑learning quickly and effectively.


Qualifications

  • An interest in applying mathematical concepts to real‑world financial problems
  • An interest in implementing theoretical insights as working code
  • A Masters or PhD degree (or be working towards one) in a highly quantitative subject, such as mathematics, statistics, computer science, physics or engineering
  • Previous financial experience is not required, although an interest in finance and the motivation to rapidly learn more is a prerequisite for working here

Why should you apply?

  • Highly competitive compensation plus annual discretionary bonus
  • Lunch provided (via Just Eat for Business) and dedicated barista bar
  • 35 days’ annual leave
  • 9% company pension contributions
  • Informal dress code and excellent work‑life balance
  • Comprehensive healthcare and life assurance

Interview process

Typical stages include four technical interviews focusing on mathematics, and, if your profile is ML‑oriented, two ML interviews covering knowledge, programming and statistics. Stage Three is leadership interviews with senior leaders. We also administer a quant quiz (either general or ML specific) and review your CV during the online application stage.


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