Thrive in a collaborative and dynamic environment where smart people learn and grow together.
Quantitative research & machine learning
Our Research Lab is a home for curious minds, where our researchers apply deep mathematical, statistical and scientific rigour to tackle some of the most complex challenges in quantitative finance.
Why join our team
Mathematical modelling
We combine cutting-edge technology with world-class resources to create algorithmic platforms for our clients.
Using rigorous scientific methods, we analyse vast, complex datasets to uncover deep, actionable insights. Our platform enables researchers to test hypotheses, build models and receive instant feedback, accelerating innovation at every step.
We then design and implement advanced optimisation techniques to extract maximum value from every idea.
Machine learning
Our researchers challenge the efficient market hypothesis every day, a task that demands more than textbook methods.
To stay ahead, they harness massive compute power and apply cutting-edge machine-learning techniques, whether drawn from the latest research or developed in-house. Innovation is essential; in a world of constant competition, only novel approaches deliver an edge.
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.
Inspirational mathematicians
Our researchers come from leading global institutions, often joining us after completing PhDs or postdoctoral work, with publications at the world’s most prestigious conferences.
We empower them with the autonomy to shape their research, supported by a collaborative and intellectually stimulating environment that values curiosity, creativity and deep thinking.
What our people say
"My internship was a hugely valuable experience that sharpened my skills and gave me a new perspective on building models with real-world impact."
"One of the things that has truly stood out to me is the collaborative and welcoming culture. I hadn’t expected such a supportive environment but it’s been one of the main reasons I’ve enjoyed working here from day one."
"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."
"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."
"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."
"There was a lot I didn't know about 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."
"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."
Quant Research
Data Scientist
London
Data Vendor Analyst
London
Natural Language Processing Researcher
London
Quantitative Analyst
London
Internship in Quantitative Research
London
Machine Learning Research Internship
London
Natural Language Processing Internship
London
Quantitative Researcher – Postgraduate
London
Machine Learning Researcher
London
Quantitative Researcher – Fundamental Equity Research
London
Quantitative Researcher – Experienced
London
Assessment process for quantitative
research and machine learning
Our quantitative researchers and ML 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
Interview preparation guide
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.
Stage one: Online quant quiz
Recommended reading
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.
Stage two: Technical interviews
Quantitative Researcher Interview Questions
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 that focus on your ML knowledge. You should also expect questions on mathematics, programming and statistics that are relevant to the space.
Stage three: Leadership interviews
Following the successful completion of the technical interviews, you will meet some of our leaders.
Latest news
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Latest events
- Quantitative engineering
- Quantitative research
Pub Quiz: Berlin
08 May 2026
Berlin - to be confirmed after registration
- Quantitative engineering
- Quantitative research
Pub Quiz: Paris
14 May 2026
Paris - to be confirmed after registration
- Quantitative engineering
- Quantitative research
Pub Quiz: Amsterdam
25 May 2026
Amsterdam - to be confirmed after registration
Other teams
We collaborate with researchers, design real-time platforms and process massive datasets at speed and scale.
We partner with and invest in the open-source community.
We identify, test and on-board the latest tech, enabling our researchers and engineers to keep innovating.
We’re hiring in quant research and ML
Ready to join a dynamic culture that rewards innovation? Discover your next career step with us.
View our roles