Quant jobs / G-Research

Quantitative Data Engineer

A data engineering role in G-Research's engineering team that takes raw datasets through to live signals. It uses large language models to automate and scale that process.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Onboard third-party datasets with pipelines, normalisation and validation
Work with researchers to engineer features and signals
Use LLM-based agents to automate ingestion-to-signal workflows
Build reusable tools that help researchers scale their work

What they ask for

Required

Good degree in a quantitative subject
Strong software engineering and data skills
Algorithms and data structures
Production data pipelines in Python
Probability and statistics on real data

Preferred

Hands-on LLM agents and workflows

Education: At least a 2:1 or equivalent in maths, statistics, CS, physics or engineering
Experience: Experience building production data pipelines; finance experience not needed
Languages and tools: Python

How to prepare

Build a pipeline in Python that ingests, validates and normalises a messy public dataset
Practise data-quality checks such as schema drift, duplicates and timestamp errors
Try an LLM-assisted data task and measure how often it is wrong
Brush up algorithms and data structures for interviews

What to study

Apply

Read the full posting on G-Research’s site before applying: requirements, location and pay can change after we check them.

View the posting on G-Research’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with G-Research and doesn’t handle applications.