1 day ago
London, United KingdomIntern
Responsibilities
- Design and deliver high-quality, maintainable production code for large and complex datasets.
- Support and evolve production platforms and quantitative research tools.
- Partner with quantitative researchers to improve data quality and value.
- Develop and optimize database queries and underlying infrastructure.
- Enhance internal tools and data processing pipelines used at scale.
- Collaborate with experienced software engineers on high-impact projects.
Requirements
- Be studying toward a 2:1 or above in Computer Science or a closely related discipline.
- Be graduating in 2028 and currently in the penultimate year of study.
- Have experience with at least one object-oriented programming language, such as C#, Java, or C++.
- Have a strong understanding of algorithms, data structures, and systems architecture.
- Demonstrate interest in engineering for quantitative research and complex systems at scale.
- Have a structured, analytical approach to problem-solving and sound judgment.
- Take a proactive approach to improving code, systems, and ways of working.
- Communicate clearly with technical and non-technical teams.
- Demonstrate collaboration and willingness to share ideas, feedback, and knowledge.
Benefits
- 12-week summer internship from 28 June 2027 to 17 September 2027.
- Working hours are 09:00–17:30.
- Structured onboarding and a dedicated experienced-engineer mentor.
- Access to internal technical and professional development courses.
- Opportunities to develop financial domain knowledge.
- Highly competitive compensation.
- Lunch provided via Just Eat for Business and access to a dedicated barista bar.
- 30 days’ annual leave pro rata.
- 9% company pension contributions.
- Informal dress code and excellent work/life balance.
- Optional private health insurance.
- Monthly company events.
- Centrally located office near five stations and six tube lines.
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.