G-Research combines quantitative research and software engineering to analyse financial markets.
Quantitative Data Engineer
As a Quantitative Data Engineer in G-Research's engineering team, based in London, you will design data pipelines and tools to support quantitative research. The role involves using Python, large-scale computing and agents based on large language models, working with quantitative researchers.
Information about G-Research
- Official domain
- gresearch.com
- Open jobs
- 70
Job details
The full description published by G-Research.
Description de l’offre
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
Requirements
- Strong software engineering and data skills
- Solid knowledge of algorithms, data structures and software fundamentals
- Experience building production data pipelines
- Strong Python data processing skills
- Comfort applying probability and statistics to real-world data problems
Benefits mentioned
- 35 days' annual leave
- 9% company pension contributions
- Comprehensive healthcare and life assurance
- Cycle-to-work scheme
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