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Quantitative Research & Machine Learning

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

Mathematical Modelling

Our technology and resources are combined to build a single, powerful algorithmic trading platform for client use.

We use rigorous scientific methodology to analyse an extensive data ecosystem, extracting deep insights from truly massive datasets. Our platform allows our researchers to test, model and get instant results. We then design and develop state-of-the-art optimisation techniques to maximise the value of every idea.

Machine Learning

Our researchers have a challenge: disproving the efficient market hypothesis every day. This requires them to harness massive compute power and to use state-of-the-art ML techniques – published in recent conferences or developed entirely in-house – as textbook methods won’t beat the competition.

Machine Learning College

We don’t just hire some of the best ML practitioners in the world, we also develop the next generation of talent too, through G-Research Machine Learning College.

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Inspirational Mathematicians

Our culture is collaborative and intellectual. Most of our researchers have joined from PhDs or Postdocs from top global institutions, and have had their work published at the most prestigious conferences in the world.

What Our People Say

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Simon Technical Signals Engineering Manager

"I continue to be blown away by the quality of the people I get to work with here: G-Research thrives because of its team culture and we’ve hired carefully to make sure everyone is both exceptionally smart and great to work with."

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Sebastian Senior Quantitative Researcher

"G-Research makes a lot of effort to have a very open culture and gives a lot of freedom to its individual researchers to pursue directions that they think are valuable, with each researcher very much driving their own research. I didn’t feel like I was losing a lot of freedom (compared to academia)."

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Yang Quantitative Researcher

"What I like the most about my job is it’s super open. I’m able to work with a lot of folks from other teams, too, such as working closely with Engineers and other Quantitative Researchers."

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Clement Quantitative Researcher

"My role focuses on finding signals in real-world data and in many ways, it feels like a continuation of my PhD; I’m looking at unexplored problems and I choose which ones to focus on."

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Leon Quantitative Research Manager

"There was a lot I didn't know about the G-Research, so I gained insights from those who interviewed me. They all came across as intelligent, curious, and interested in exploring problems from different angles. I figured if people like this enjoy their jobs then I most certainly will."

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Fabian SENIOR QUANTITATIVE RESEARCHER

"The two biggest things that I like about working at G-Research are the smart and incredibly friendly colleagues, as well as being able to strike a really good work-life balance (in contrast to a lot of the finance industry)."

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Our Opportunities

Thrive in a collaborative, flexible environment where smart people learn and grow together.

Assessment Process for Quantitative
Research and Machine Learning

Our quantitative researchers and machine learning practitioners have a record of academic achievement in mathematics, physics, ML, computer science or engineering. There’s no need for experience in finance.

Online Application

Quick and easy: We will ask for your CV/resume and a few personal details like your education and contact information. Our Talent Acquisition team will review your application to see if you are a good fit and you will receive an update on the status of your application within one week of applying.

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Stage One: Online Quant Quiz

You will be asked to complete one of two quant quizzes; either a general quantitative aptitude assessment, or an ML specific one, depending on your background.

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Stage Two: Technical Interviews

Typically, you will sit four interviews, one of which will focus on in-depth technical questions in mathematics. Each interview will last one hour.

If your profile is better suited to ML, you’ll complete two one-hour interviews, which will focus on your ML knowledge, but do expect to answer questions on mathematics, programming and stats that are relevant to the ML space as well!

Stage Three: Leadership Interviews

Following the successful completion of the technical interviews, you will meet some of our leaders.

Take the Next Step in Your Career

Looking to make an impact at one of the world’s leading quantitative research and technology firms? See our open roles and apply now.

Latest news

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G-Research 2024 PhD prize winners: Imperial College London
  • 18 Jun 2024
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G Research
G-Research May 2024 Grant Winners
  • 06 Jun 2024

Each month, we provide up to £2,000 in grant money to early career researchers in quantitative disciplines. Hear from our April grant winners.

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G-Research 2024 PhD prize winners: University of Oxford
  • 03 Jun 2024
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Latest events

  • Machine Learning
  • Quantitative Research

Eastern European Machine Learning (EEML) Summer School

15 Jul 2024 - 20 Jul 2024 Naučno Tehnološki Park, University of Novi Sad, Fruškogorska 1, Novi Sad, Serbia
  • Machine Learning
  • Quantitative Research

MLx Representation Learning and Generative AI

11 Jul 2024 - 14 Jul 2024 Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter (550), Woodstock Road, Oxford, OX2 6GG
  • Quantitative Research

Barcelona Quant Challenge

27 Jun 2024 - 27 Jun 2024 H1898 Hotel - Barcelona  La Rambla, 109, Ciutat Vella, 08002 Barcelona, Spain

Other teams

Engineering

We collaborate with researchers, design real-time platforms and process massive datasets at speed and scale.

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Open-Source Software

We partner with and invest in the open source community.

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Technology Innovation Group

We identify, test and on-board the latest tech, enabling our researchers and engineers to keep innovating.

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