Quantitative Researcher - Postgraduate

Reposted 9 Days Ago
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London, Greater London, England
In-Office
Entry level
Big Data • Fintech • Information Technology • Machine Learning • Financial Services
The Role
G-Research seeks a Quantitative Researcher to use machine learning and statistical methods to analyze global financial markets. A Master's or PhD in a quantitative field is preferred, but prior finance experience is not necessary.
Summary Generated by Built In

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 them to harness massive compute power and use state-of-the-art ML techniques to find innovative solutions, as textbook methods won’t beat the competition.

This is a pure research role where you will be able to 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 be able to take advantage of a learning experience tailored to accelerate your knowledge and expertise in machine learning quickly and effectively.

Find out more about the G-Research ML College.

Who are we looking for?

The ideal candidate will have:

  • 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
  • Cycle-to-work scheme
  • Monthly company events

G-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas-driven business and we place great value on diversity of experience and opinions.

We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section

Top Skills

Machine Learning
Statistical Analysis
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The Company
Dallas, TX
1,039 Employees
Year Founded: 2001

What We Do

G-Research is a leading quantitative research and technology firm, with offices in London and Dallas.

We hire the brightest minds in the world to tackle some of the biggest questions in finance. We pair this expertise with machine learning, big data, and some of the most advanced technology available to predict movements in financial markets.

We take pride in our dynamic, flexible and highly stimulating culture where world-beating ideas are prized and rewarded. We employ some of the best people in their field and are keen to nurture their talent in a supportive working environment.

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