3 days ago
London, United KingdomMid Level
Responsibilities
- Onboard new third-party datasets and build pipelines, normalization, and validation processes that make them research-ready.
- Partner with Quantitative Researchers to engineer features and build signals from onboarded data.
- Use LLM-based agents and workflows to safely automate the pipeline from ingestion to signals.
- Build tools and reusable workflows that help researchers and data scientists scale their work.
Requirements
- A minimum 2:1 degree or equivalent in a quantitative subject such as mathematics, statistics, computer science, physics, or engineering.
- Strong software engineering and data skills, including knowledge of algorithms, data structures, and software fundamentals.
- Experience building production data pipelines with strong Python data processing skills.
- Ability to apply probability and statistics to real-world data problems.
- Motivation to deliver measurable value and preference for collaborative, innovative, proactive, and flexible environments.
- Hands-on experience with LLM-based agents and workflows is desirable.
- Finance experience is not required; candidates from non-financial backgrounds are encouraged to apply.
Benefits
- Highly competitive compensation plus an annual discretionary bonus.
- Lunch provided via Just Eat for Business and a dedicated barista bar.
- 35 days of 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 and all-expenses-paid experience days.
- Inclusive work environment with accommodations available for applicants with disabilities or special needs.
Tech Stack
Categories
Data Engineering
About G-Re
G-Research is a London-based quantitative research and technology firm that develops models, data pipelines, and trading systems to forecast movements in global financial markets. It employs researchers and software engineers to build machine-learning-driven strategies and the infrastructure that supports systematic investing, spanning high-performance compute and secure networks. Privately held and founded in 2001, the company operates from its London headquarters and focuses on institutional, data-intensive finance.