2027 - Internship, Quantitative Research and Trading
Qube RT·London·United Kingdom·Hedge Fund & Quant
Qube RT is hiring a 2027 - Internship, Quantitative Research and Trading in London. Posted 2026-09-09; applications close 2026-11-08 (in 59 days).
Role details
Programmes
- Final-year internship, penultimate-year internship, and some permanent opportunities
- Programme duration: 4–6 months, starting in 2027
- Locations: Aarhus, Budapest, Dubai, Geneva, London, Paris, Zurich
Who qualifies
Penultimate or final-year students completing a bachelor’s, master’s, or PhD degree.
About Qube Research & Technologies (QRT)
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.
Research is central to how QRT invests. Over the years, we have built a global research and execution platform spanning geographies, asset classes and trading horizons, from high to low frequency. This gives researchers access to large and diverse datasets, sophisticated research tools, and the infrastructure needed to turn research ideas into live trading strategies.
Our internships are designed to give students meaningful experience of that process. You’ll join a systematic team, work on real research or trading problems, and learn from experienced researchers and traders. The environment is rigorous and collaborative: ideas are tested against data, assumptions are challenged, and good questions matter as much as quick answers.
Your future role at QRT
Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on, with the aim of finding the strongest fit.
As a Quantitative Research Intern, you could contribute in one of two complementary areas within one of QRT’s systematic teams, spanning high, mid and low frequencies:
Research
Your focus will be on developing predictive signals from large and varied datasets. You’ll explore the data for patterns and form hypotheses about what might be driving them. From there, research is iterative: you’ll design tests, question the results, adjust your approach and test again. Working with other researchers, you’ll learn to distinguish promising signals from noise. In doing so, you’ll experience the full research process—from an initial observation to something that can be used in live trading.
Trading
You’ll contribute to the live deployment of QRT’s research by working directly with our systematic trading platform. You’ll monitor how signals behave in production, track performance, improve execution efficiency, and help identify and manage potential risks. Working closely with senior Researchers and Traders, you’ll investigate how strategies behave in production and look for ways to make them more robust and scalable. You’ll use quantitative analysis and programming to understand what is happening in live systems and determine where improvements can be made.
Across both areas, how you approach a problem matters. We’re looking for interns who are curious, creative and collaborative. You should be comfortable exploring ideas, asking questions and learning as you go.
Your present skillset
- Academic background: Pursuing an advanced degree in a quantitative field such as Data Science, Statistics, Mathematics, Physics or Engineering.
- Quantitative foundations: Strong analytical skills and an interest in using mathematics, statistics and computation to understand complex problems.
- Programming: Coding experience in at least one leading programming language, including Python, C++ or C#.
- Research interests: Knowledge of statistics, machine learning, NLP or AI techniques is useful but not essential.
- Data: Experience exploring large datasets across multiple time horizons is a plus.
- Problem solving: Able to work through complex problems rigorously while maintaining strong attention to detail.
- Independence and collaboration: Comfortable working autonomously while exchanging ideas and working closely with colleagues from different disciplines and backgrounds.
- Communication: Able to explain your reasoning and communicate technical ideas clearly.
- Languages: Fluent in English; additional languages are a plus.
Interviewing
- Apply Online: Submit your application online. Applications are reviewed on a rolling basis by our Talent Acquisition team. Thoughtful answers that explain your interests and motivations are useful.
- Technical Assessment: Selected candidates will complete a coding challenge focused on core programming and problem-solving skills.
- Interviews: Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your quantitative and technical thinking, how you approach unfamiliar problems and how you work with others.
We also encourage candidates to take part in one of our Data Challenges. These are an opportunity to work on problems relevant to quantitative research and demonstrate your analytical and technical approach. Strong performance may lead to direct follow-up from our team: Challenge data (ens.fr).
QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees to achieve a healthy work-life balance.
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Applying to this role
This 2027 - Internship, Quantitative Research and Trading role at Qube RT runs through the firm's own careers portal and expects a CV and cover letter written specifically for the posting, not a portable submission carried across firms. Jorb AI's application agent tailors a CV and cover letter from your background to this posting and tracks the role alongside the rest of your applications.
Jorb AI tracks details for 2027 - Internship, Quantitative Research and Trading at Qube RT. Postings refresh hourly from primary careers pages. Job details mirror the firm's posting; the apply link goes directly to the source. Last refreshed 2026-09-10.
