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  • Quantitative Research
  • London

Do you want to tackle the biggest questions in finance with near infinite compute power at your fingertips?

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

We are proud to employ some of the best people in their field and to nurture their talent in a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded.

This is a role based in our new Soho Place office – opened in 2023 - in the heart of Central London and home to our Research Lab.

The role

The Data Intelligence team sits within our Research function and plays a critical role in managing the firm’s data assets. The team oversees the full lifecycle of data products — from discovery and delivery to ongoing stewardship and commercial oversight — acting as the central link between our quantitative research teams and external data providers.

As a Data Vendor Analyst, you will help curate and maintain a comprehensive knowledge base covering global financial and related data domains. This ensures that data sources are easily discoverable, consistently categorised, well-documented and accessible to stakeholders across the business.

We are seeking a well-organised and technically adept individual to take ownership of this knowledge base. You will be instrumental in scaling our data intelligence capabilities to match the rapid expansion of both the external data landscape and our internal appetite for data.

Success in this role requires close collaboration with quantitative researchers, data scientists and engineers, as well as regular interaction with legal and commercial teams across and beyond the organisation. You will need a strong understanding of research workflows, data lifecycles and the commercial aspects of data acquisition and management. Familiarity with the financial data ecosystem and hands-on experience with cataloguing tools and best practices is essential.

Key responsibilities of the role include:

  • Documenting the relevance, quality and reliability of data sources for quantitative analysis

  • Designing, implementing and maintaining a robust framework for gathering and storing up to date information on the financial data industry

  • Categorising vendor documentation, supporting white papers and other relevant literature

  • Managing tooling to improve the discoverability of information within these resources

  • Assisting the data engineering team in integrating newly acquired products into the data infrastructure

  • Collaborating with data stakeholders to improve insights into the company’s data estate

Who are we looking for?

The ideal candidate will have the following skills and experience:

  • A background in finance, mathematics, computer science or a related field

  • Experience dealing with third party suppliers, particularly in the data and software industries

  • A strong knowledge of financial instruments, markets and data sources

  • Organised with an analytical mindset

  • Strong communication and collaboration skills

  • Knowledge of data cataloguing and data visualisation tools, such as Tableau, is a plus

Why should you apply?

  • Highly competitive compensation plus annual discretionary bonus

  • Lunch provided (via Just Eat for Business) and dedicated barista bar

  • 30 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
Apply Now
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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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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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Willy Data Services Manager

"My team and I have access to a wide range of training opportunities, which allowed us to get the entire team AWS certified within a quarter. We’re actively working on the latest AI and machine learning projects to stay ahead of industry standards."

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Gabriel Software Engineer

"The problems we solve are often novel in nature, meaning we get to solve the previously unsolved. I find this to be a great way to stay challenged and engaged!"

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Yoga Software Engineering Manager

"The friendly, collaborative atmosphere here is a breath of fresh air and a perfect fit for me."

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Garrett Software Engineer

"The willingness to collaborate between both teams and functions has made the transition into my new role as easy as possible."

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Michael Software Engineer

"It’s a privilege to be in a place where my curiosity is nurtured and my learning journey is supported!"

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Joshua Platform Engineer

"The best thing about working at G-Research is being around such smart people, it motivates you to always want to grow and learn."

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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.

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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.

Data Vendor Analyst Apply now

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