2027 - Internship, Data Engineering
Qube Research & Technologies
- Location
- Paris, London
- Employment
- Internship
- Work model
- On-Site
- Level
- Intern
- Posted
- 2h ago
Skills
About this role
Programme duration: from 5 to 6 months, starting in 2027.
Who qualifies: Penultimate or final year students completing a Bachelor's, Master's.
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across liquid asset classes and markets worldwide. Our approach to investing is scientific: we bring together data, research, technology and trading expertise to develop and run systematic strategies.
Technology and data are central to how QRT works. Over the years, we have built a global research and execution platform spanning geographies, asset classes and trading horizons, from ultra-low-latency systems to large-scale research, analytics and data infrastructure. We invest heavily in engineering, automation and scalable systems because better technology allows us to test ideas faster, operate more reliably and tackle harder problems.
Our internships are designed to give students meaningful experience of that work. You’ll join a team, contribute to real projects and work alongside engineers, researchers and traders on problems that matter to our research and trading activities. The environment is technical and collaborative, with plenty of scope to ask questions, test ideas and take ownership
Your future role at QRT
As part of QRT’s data teams, you’ll work on the systems and datasets behind quantitative research and trading. You’ll collaborate closely with traders, researchers and engineers, tackling problems across data acquisition, engineering and platform design.
Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on. Depending on the strongest fit, your internship may focus on one of the following areas:
• Quantitative Data Analyst – Source and evaluate new datasets based on priorities from our trading desks. You’ll explore how new data can support research, manage sourcing projects from acquisition through to design, and work with Data Engineers to bring useful datasets into production at scale.
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