Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

2026 - Internship, Quantitative Developer

Qube Research & Technologies
London
3 days ago
Applications closed

Related Jobs

View all jobs

Data Science Internship 2026

Data Strategy & Transformation - Undergraduate Placement 2026

Optimization, Analytics & Recruitment Solutions Data Analytics Undergraduate

Optimization, Analytics & Recruitment Solutions Data Analytics Undergraduate...

Data Governance Analyst

Head of BI/Business Intelligence - Microsoft

Programme duration: from 5 to 6 months, starting in 2026.

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 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 Developer at QRT, you will contribute to the engineering solutions that power our world-class quantitative research and trading, building the tools, platforms, and infrastructure that enable researchers and traders to operate at their best. You will be tackling projects that demand both technical depth and creativity.

Examples of the projects you may work on include:

  • Trading Infrastructure & Low-Latency

Build and optimize the high-performance systems that power QRT's real-time trading. Contribute to low-latency infrastructure, execution logic, and live monitoring tools — where engineering performance directly impacts trading outcomes. These roles involve hands-on development in C++ or .NET, close to production and tightly integrated with live strategies.

  • Research Enablement & Platform Engineering

Develop and optimize the platforms that power quantitative research across the firm. This may include scalable APIs, machine learning and data pipelines, orchestration frameworks, and shared infrastructure that accelerates research and experimentation. Collaborate closely with researchers to create efficient, reliable, and standardized environments for innovation.

  • Tooling & Workflow Automation

Design and deliver internal tools used directly by traders and researchers on discretionary desks. Projects may involve streamlining workflows, improving data accessibility, and supporting real-time decision-making - all within the high-intensity environment of front-office operations. Work interactively with users to deliver intuitive, high-impact solutions.

  • Monitoring & Analytics Tools

Build tools and dashboards to support the firm's risk and oversight functions, enabling performance evaluation, risk monitoring, and investment oversight. Combine strong data processing and visualization skills with scalable infrastructure, and explore opportunities to integrate applied machine learning for deeper insights.

  • Core Trading Systems (London only)

Build and maintain the infrastructure supporting the development, testing, and deployment of trading signals in production. This includes tooling for signal generation, model evaluation, data ingestion, and analytics - enabling systematic trading teams to iterate, validate, and implement live trading logic efficiently and reliably.

Your present skillset

  • Strong core computer science foundations, including algorithms, data structures, parallel programming, and object-oriented programming (OOP).
  • Genuine interest in software engineering, infrastructure, or data engineering within a low-latency environment, working in C++, C#, or Python.
  • Interest to build expertise in high-performance, real-time trading systems
  • Excellent communication and analytical skills – you will interact directly with Traders and Researchers
  • Drive for rapid autonomy and the ability to work in a fast-paced, high-performance setting.
  • Rigorous and structured approach to problem-solving.

Preferred qualifications (a plus):

  • Knowledge of databases such as SQL or NoSQL.
  • Experience in front-end development.
  • Interest in financial markets and/or algorithmic trading.

Interview Process

  • Application - Submit your application online. We review applications on a rolling basis, so we recommend applying early to maximize your chances.
  • Technical Assessment - Selected candidates will be invited to complete a coding challenge designed to evaluate core technical and problem-solving skills.
  • Interviews - Shortlisted applicants will proceed to interviews, conducted either on-site or via Microsoft Teams. These will assess both your technical expertise and your alignment with our culture and values.

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.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.