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Quantitative Analyst

  • Quantitative Research
  • London

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. We build smart strategies that win over time.

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

With access to large scale data and compute, our Quant Analysts review and refine client trading behaviour to enable new opportunities and maximise performance.

You will work closely with other Research teams, as well as those in Engineering and Front Office, to make improvements, respond to external changes and identify new opportunities across a complex, global client trading platform. Attention to detail and communication is key.

You will perform post-trade analysis in Python using large scale data and compute, implement performant production C# code in the trading platform and monitor your changes in the real-world.

Your work will range between medium term strategic projects and short-term urgent tasks - prioritisation skills and pragmatic decision making to deliver commercial value are necessary.

Who are we looking for?

The ideal candidate will have the following skills and experience:

  • Demonstrable experience in a quantitative role working at pace with an excellent performance track record
  • An appreciation of market microstructure and algorithmic order placement behaviour
  • Strong coding skills, ideally Python and C#, but other languages are welcome
  • The ability to question the status quo and drive improvement and changes
  • A strong interest in finance and the motivation to rapidly learn and deliver

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
Location: London
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Leon Quantitative Research Manager

"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."

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What our people say

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Matteo Quantitative Research Intern

"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."

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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 Senior 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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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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Margot HRIS manager

"I enjoy how dynamic the work environment at G-Research is. It keeps you busy and continuously creates opportunities to develop yourself and your career, too."

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Mario FPGA Manager

"While some people might think working in finance may not be too exciting, at G-Research, it is, especially if you see it as a problem to solve. How do we solve this algorithm? How do we get faster? This is why I think people are really excited to work here."

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Alexander Software Engineer

"I've felt very lucky to work with teams of people across the business who are generous with their time, knowledge and ideas as we collaborate to continuously build and rebuild complex systems with lots of moving parts."

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Simon Cyber Security Manager

"There are lots of people within the business that have started as a junior and progressed – which I think is testament to G-Research's belief in fostering growth and recognising potential."

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Mia Software Engineer

"What I appreciate most about working in G-Research is the supportive and knowledgeable environment. Everyone is incredibly helpful and patient, which ensures there’s a good balance between being challenged and your workload."

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Interview process

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.

Interview preparation guide
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.

Recommended reading
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.

Quantitative Analyst Apply now

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