QR
Qube Research And Technologies
Research Scientist

2026 - Internship, Quantitative Research/Trading

On-siteJuniorResearch Scientistposted 1mo ago
Role summaryAI-generated

Quantitative research internship at a global systematic investment firm, focusing on developing data-driven trading strategies across asset classes using advanced statistical and ML techniques.

Skills required

About this role

Programme duration: From 4-6 months, starting in 2026. Most individuals join in April, May, or June of each year.

Who qualifies: Penultimate or final year students completing a Bachelor's or a Master's degree.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. 

Over the years, QRT has invested in a global research and execution platform which has been deployed to cover all geographies and asset classes. This platform covers a broad spectrum from high to low frequency trading systems. We thrive at the intersection of cutting-edge technology, smart automation, and scalable processes, enabling us to move fast, think big, and deliver at scale.  

We are committed to identifying and developing exceptional talent, and are inviting a new cohort of outstanding individuals to join us in the year ahead. Our internship offers a stimulating, intellectually rigorous, and high-performance environment, where collaboration is key to success. You will work alongside and be mentored by industry-leading professionals, gaining invaluable experience and positioning yourself for the opportunity to secure a full-time graduate role upon successful completion of the program.

Your future role at QRT

Throughout the recruitment process, we will work to align your skills, interests, and potential with the teams where you can make the greatest impact.

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 core objective will be to develop high-quality predictive signals. You will leverage access to vast and diverse datasets to identify hidden statistical patterns and market opportunities. Collaborating with fellow researchers to exchange ideas and refine methodologies. You will be trained to lead the full research cycle - from idea generation to implementation.

Trading

You will contribute to the live deployment of QRT’s research by working on the systematic trading platform itself. This involves monitoring signal behaviour, tracking performance, and improving execution efficiency, while also helping to identify and manage potential risks. Working closely with senior Researchers and Traders, you will focus on refining and scaling systematic processes, applying your quantitative and programming skills to ensure strategies perform optimally in production.

We’re looking for interns who are curious, creative, and collaborative. If you’re passionate about learning, excited to take on challenges, and ready to make a real impact, you’ll find plenty of opportunities to grow with us.

Your present skillset

  • Pursuing an advanced degree in a quantitative field such as data science, statistics, mathematics, physics, or engineering
  • High level of technical knowledge in statistics, machine learning, NLP or AI techniques is a plus
  • Coding skills required in at least one leading programming language (Python and C++ or C#)
  • Experience in exploring large datasets across multiple time frames is a plus
  • Capacity to multi-task in a fast-paced environment while keeping strong attention to detail
  • Ability to work autonomously, in a collegial and collaborative setting, and with colleagues from diverse backgrounds and areas of expertise.
  • Excellent communication skills
  • Fluent in English, any other language is a plus

Interviewing:

  • Apply online: applications are evaluated on a rolling basis by a member of our Talent Acquisition team. This is a great opportunity to stand out, as we read every application carefully and look for specific, thoughtful answers that reflect your genuine interests.
  • Interviews conducted on-site or through Teams allow us to evaluate your technical abilities and how well you align with our company culture.

We encourage you to take part in one of our Data Challenges, which offer a valuable opportunity to engage with the types of problems encountered in the Quantitative Research role while showcasing your analytical and technical skills. Strong performance may lead to direct follow-up from our team, making it an excellent way to gain early visibility in the recruitment process: 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 achieve a healthy work-life balance

Similar open roles

G
NEW

Senior Applied Research Scientist

GEICO·Bethesda, MD; New York City, NY; Palo Alto, CA
On-siteSeniorResearch Scientist
$115k – $230k USD
2d ago
TS
NEW

Senior Applied Machine Learning Scientist, Predictive AI(B3617)

TD Securities·Toronto, Ontario; Montréal, Québec
On-siteSeniorResearch Scientist
$157k – $190k USD
2d ago
SS
NEW

Quantitative Investment Researcher (Assistant Vice President)

State Street·Cambridge, Massachusetts
On-siteSeniorResearch Scientist
$175k USD
2d ago
Z
NEW

Staff Machine Learning Scientist

Zendesk·Tallinn, Estonia; Krakow, Poland
On-siteStaffResearch Scientist
2d ago
H

Research Scientist for Power Electronics

Hitachi·Vaesteras, Vastmanland County, Sweden
On-siteSeniorResearch Scientist
5d ago