Quantitative Data Engineer

G-Research; Greater London; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Competitive compensation

Lunch provided

35 days annual leave

9% company pension contributions

Healthcare and life assurance

Monthly company events

Job summary

G-Research in London HQ is seeking a Quantitative Data Engineer who will take data from raw sources through to live signals, working with Quant researchers to engineer features and build scalable pipelines. You will join a team that values collaboration and methodological execution to accelerate discovery.

You will use Python on large-scale compute, apply probability and statistics to real data, and explore LLM-based agents to automate the end-to-end data ingestion to signals, contributing to a

Qualifications

• Minimum 2:1 degree in a quantitative subject such as mathematics, statistics, computer science, physics or engineering.
• Strong software engineering and data skills.
• Experience building production data pipelines with Python data processing.
• Solid knowledge of algorithms, data structures and software fundamentals.
• Comfort applying probability and statistics to real-world data problems.

Responsibilities

• Onboarding new third-party datasets, building pipelines, normalization 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.

Skills

Python

Data pipelines

Algorithms

Statistics

Software engineering

LLM workflows

Collaboration

Education

2:1 degree in quantitative field

Tools

Python

Job description

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