Global Quant Research Intern: Data & Signals

targetjobs UK; Aarhus; On-site; DKK 100,000 - 167,000; Full time

Job summary

Qube Research & Technologies (QRT) invites penultimate- and final-year students to join our systematic teams in a 4–6 month internship starting in 2027. You’ll work on real research and trading problems across high, mid, and low frequencies, with mentors and peers in a rigorous, data-driven environment.

Locations include Aarhus, London and other global hubs; you’ll gain hands-on experience in research or trading, developing practical skills in data analysis, programming, and model validation

Qualifications

• Penultimate or final-year student pursuing a bachelor’s, master’s or PhD.
• Strong analytical and quantitative skills with passion for data-driven research.
• Experience with Python, C++ or C# programming.
• Interest in statistics, machine learning, NLP, or AI is beneficial.
• Comfort with exploring large datasets across time horizons.

Responsibilities

• Develop predictive signals from large datasets.
• Design and test hypotheses; iteratively evaluate results.
• Collaborate with researchers and traders to deploy models.
• Monitor signals, track performance, and identify risks in production.
• Communicate findings clearly to the team.

Skills

Academic Background

Quantitative Foundations

Programming

Research Interests

Data

Problem Solving

Independence and Collaboration

Communication

Languages

Education

Pursuing an advanced degree in a quantitative field (Data Science, Statistics, Mathematics, Physics or Engineering)

Tools

Python

C++

C#

Job description

Qube Research & Technologies (QRT) invites penultimate- and final-year students to join our systematic teams in a 4–6 month internship starting in 2027. You’ll work on real research and trading problems across high, mid, and low frequencies, with mentors and peers in a rigorous, data-driven environment.

Locations include Aarhus, London and other global hubs; you’ll gain hands-on experience in research or trading, developing practical skills in data analysis, programming, and model validation