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
Read on to find out what you will need to succeed in this position, including skills, qualifications, and experience.
- 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 roleQuantitative 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-readyPartnering with Quantitative Researchers to engineer features and build signals from onboarded dataUsing LLM-based agents and workflows to safely automate the pipeline from ingestion to signalsBuilding tools and reusable workflows that help researchers and data scientists scale their workWho 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 engineeringA combination of strong software engineering and data skillsSolid knowledge of algorithms, data structures and software fundamentalsExperience building production data pipelines, with strong Python data processing skillsComfort applying probability and statistics to real-world data problemsMotivation from seeing your work deliver measurable valueA preference for highly collaborative environments that value innovation, proactivity and flexibilityHands-on experience of LLM-based agents and workflows is desirableYou 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 bonusLunch provided (via Just Eat for Business) and dedicated barista bar35 days' annual leave9% company pension contributionsInformal dress code and excellent work/life balanceComprehensive healthcare and life assuranceCycle-to-work schemeMonthly company eventsExperience 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. xsabvtc
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 sectionSummaryLocation: London, UKType:
Quantitative Data Engineer in Vauxhall employer: G Research
At G-Research, we pride ourselves on being an exceptional employer, offering a dynamic work environment in the heart of London where innovation thrives. Our commitment to employee growth is evident through mentorship opportunities, comprehensive healthcare, and a strong focus on work-life balance, all while fostering a culture that values diversity and collaboration. Join us to tackle complex challenges in cyber security and be part of a team that not only values your contributions but also invests in your future.
