AI-Driven Quant Data Engineer

Barlowe LLP; Greater London; On-site; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Lunch provided

35 days annual leave

9% company pension contributions

Healthcare

Life assurance

Cycle-to-work

Monthly company events

Experience days

Job summary

G-Research in London seeks a Quantitative Data Engineer to transform raw data into live signals, working alongside Quant Researchers to engineer features and signals from onboarded data. You will use Python on large-scale compute and cutting-edge infrastructure, applying LLM-based agents to automate pipelines from ingestion to signals, and contribute reusable tools to scale research.

This role emphasizes collaboration, rigorous software engineering, and delivering measurable value in a

Qualifications

• Strong academic record with a 2:1 degree in a quantitative field.
• Combination of software engineering and data skills.
• Solid knowledge of algorithms and data structures.
• Experience building production data pipelines with Python data processing.
• Ability to apply probability and statistics to real-world data problems.
• Motivation to deliver measurable value in collaborative environments.
• Desirable experience with LLM-based agents and workflows.

Responsibilities

• Onboard new third-party datasets, build pipelines, normalize and validate data.
• Partner with researchers to engineer features and build signals.
• Use LLM agents and workflows to automate pipeline from ingestion to signals.
• Develop tools and reusable workflows to scale research teams.

Skills

Python

Data pipelines

LLM workflows

Software fundamentals

Statistics

Education

2:1 degree or equivalent in a quantitative subject

Tools

SQL

Spark

Pandas

Job description

G-Research in London seeks a Quantitative Data Engineer to transform raw data into live signals, working alongside Quant Researchers to engineer features and signals from onboarded data. You will use Python on large-scale compute and cutting-edge infrastructure, applying LLM-based agents to automate pipelines from ingestion to signals, and contribute reusable tools to scale research.

This role emphasizes collaboration, rigorous software engineering, and delivering measurable value in a