2027 - Internship, HR Technology

Skills this role screens for

About the role

2027 - Internship, HR Technology

Programmes offered: Final-year internship, penultimate-year internship

Location: London

Programme duration: 3-6 months internship, starting in 2027

Who qualifies: Penultimate or final-year students completing a bachelor’s or master’s degree

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 is 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 risk 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 learn from engineers, researchers and traders working on live problems. The environment is technical, collaborative and demanding, with plenty of scope to ask questions, test ideas and take ownership. Strong performance during the internship may lead to consideration for a full-time graduate role.

Your future role at QRT

Throughout recruitment, we will work to align your skills, interests, and potential with teams where you can make the greatest impact. We are recruiting across two internship tracks:

HR Data Analytics

With mentoring from experienced engineers, help build the HR analytics platform, transforming raw data into clean, accessible formats. Work across business areas to deliver insights for managers, business partners, and senior leaders.

Examples of the projects you may work on include:

HR Software Engineer

Build full-stack applications and integrations connecting core HR systems to the wider business, from conception to production. Translate HR requirements into scalable, cloud-native tools with clean code and sound data models. Automate repetitive work to improve employee experience and free HR colleagues for judgement, creativity, and human conversations.

Examples of the projects you may work on include:

• Build, deploy and maintain scalable, secure pipelines using AWS S3, ECS and Lambda; centralise Workday and Greenhouse data in warehouses for BI tools.
• Build Python and Kotlin services to automate workflows; test, monitor and troubleshoot data flows for accuracy.
• Partner with HR, analytics engineers and leadership to align technical capabilities with business needs and deliver actionable insights.
• Develop interactive BI dashboards using tools such as Python Dash.
• Document pipelines, models, transformations and data assets, including ETL documentation and metric glossaries; uphold data security, compliance and access controls.
• Build internal tools beyond standard platform configuration, with interfaces using React, Python Dash or similar, and secure APIs and middleware connecting HR and corporate systems.
• Synchronise employee data using AWS S3, ECS and Lambda; automate manual processes in Python and Kotlin to reduce overhead and data entry errors.
• Test automation and implement error handling, logging and monitoring so integrations are reliable and trusted without manual checks.
• Translate HR logic into technical specifications, document tools and meet GDPR and financial services security standards.
• Work with functional analysts and stakeholders to identify friction in the employee lifecycle and propose software solutions.

Who they want

Your current skillset

Additional requirements — HR Data Analytics

Additional requirements — HR Software Engineering

• A degree in a numerate, scientific or computing discipline; equivalent practical experience is welcome for Data Analytics.
• A solid grounding in Python for automation, data or applications; object-oriented design for Software Engineering.
• Data modelling: metrics and semantic layers for BI in Data Analytics; SQL and models for transactional applications and analytical reporting in Software Engineering.
• Cloud familiarity, ideally AWS: willingness to learn storage and pipelines for Data Analytics; hands-on application deployment and operation, ideally with S3, Lambda or ECS, for Software Engineering.
• An analytical approach, clear communication, and enthusiasm for collaborating with technical and non-technical colleagues.
• Exposure to ETL concepts or tools through study, internships or personal projects.
• Experience with Kotlin or another statically typed JVM language.
• Front-end experience with JavaScript, HTML and CSS; familiarity with React, Bootstrap or Python Dash.
• Understanding of REST and SOAP APIs, JSON, XML and data transformation.

Nice to have

Nice to have

• Exposure to Workday, Greenhouse, employee lifecycle data or HR metrics such as retention, engagement and performance.
• Infrastructure as code, particularly Terraform.
• Experience integrating AI, LLMs or agents, understanding their strengths and limitations.
• Data Analytics: front-end or user-experience skills, including Python Dash or React.
• Software Engineering: Git and CI/CD pipelines.

The process

Interview Process

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.

• Application – Submit your application online. We review applications on a rolling basis, so applying early is recommended.
• Technical Assessment – Selected candidates will complete a technical interview with the relevant team.
• Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your technical foundations, how you reason through engineering problems and how you work with others.