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G-Research

Quantitative Data Engineer

G-Research

London

Mid-level

DataLLM / GenAIPython

Last seen 2h ago

Posted
1w ago

Posted on 22 October 2026

Workplace
Not specified

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Salary
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Listing history No signals observed

First seen 22 Oct 2026. Last checked 29 Oct, 10:17 UTC. We read each employer's own career page on a cycle and record what changes; this is what we observed, not a verdict on the role.

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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.

As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm.

Take the next step in your career.

The role

Quantitative Data Engineers take data from its raw source through to live signals, working alongside Quantitative Researchers at each step in between.

We are using large language models to automate and scale this process, so that we can take on more data than any team could handle by hand. The work is already underway. You will work in Python on large-scale compute and industry-leading infrastructure, with access to leading internal and external models.

AI is part of how every team here works, accelerating thinking and delivering impact. All colleagues are expected to bring AI into their daily workflows.

Key responsibilities of the role include:

Onboarding new third-party datasets, building the pipelines, normalisation and validation that make them research-ready

Partnering with Quantitative Researchers to engineer features and build signals from onboarded data

Using LLM-based agents and workflows to safely automate the pipeline from ingestion to signals

Building tools and reusable workflows that help researchers and data scientists scale their work

Who are we looking for?

The ideal candidate will have the following skills and experience:

A strong academic record, including a minimum 2:1 degree or equivalent in a quantitative subject such as mathematics, statistics, computer science, physics or engineering

A combination of strong software engineering and data skills

Solid knowledge of algorithms, data structures and software fundamentals

Experience building production data pipelines, with strong Python data processing skills

Comfort applying probability and statistics to real-world data problems

Motivation from seeing your work deliver measurable value

A preference for highly collaborative environments that value innovation, proactivity and flexibility

Hands-on experience of LLM-based agents and workflows is desirable

You don't need to have all of the above to apply. Finance experience is not necessary for this role and candidates from non-financial backgrounds are encouraged to apply.

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

Experience days: all-expenses-paid, bucket-list outings with colleagues, from Michelin-star tasting menus to European day trips.

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

About G-Research

G-Research hires almost exclusively out of London. It's a quant research firm, not a bank or a trading venue — the roles here are close to the research itself, and the bar reflects that.

Apply at G-Research