Heading

Welwyn, England

Internship

Onsite

Intern

Roche is a global research-focused healthcare group dedicated to advancing medicines and improving patient care. This industrial placement offers students hands-on experience across data management, analytical data science, biostatistics, real-world and clinical data strategy, and quantitative clinical pharmacology, supporting clinical data quality, analysis, reporting, and decision-making.

Apply Now

Responsibilities

DQLs oversee the quality, integrity, and availability of clinical trial data, ensuring it is fit for purpose and ready for analysis by our statisticians. Working with multiple functions, DQLs manage the design and implementation of the study database, and oversee data collection and data cleaning strategies. As a DQL, you will be a key member of the clinical study team, and your day to day work will be divided between data and people - solving novel data problems, but also learning to lead & influence others
Technical Excellence acts as the key link between the clinical data management team and technical Informatics (IT) colleagues. Rather than working directly on clinical trials, the focus is on understanding user needs and helping to shape the tools, products, and processes that streamline daily work. This role involves listening to business challenges, gathering user feedback, and translating ideas into technical solutions
Functional Excellence Specialists play a key role in helping our Data Management group improve how we manage clinical trial data by bridging the gap between new technology and the people who use it. This non-technical role focuses on change management, and making processes more efficient, consistent and scalable. You will gain hands-on experience in knowledge management, and learn how to improve the quality and longevity of our tools, ensuring they effectively support our colleagues in their day to day work
Analytical Data Scientists (ADS) are responsible for providing analytical and programming expertise for the reporting and analysis of clinical trials and related submissions to Health Authorities worldwide. We work closely with other members of Data Sciences, in particular biostatistics and data management, to ensure quality and integrity of study data. We also collaborate with other functional experts to determine appropriate analysis of data for respective disease areas
The Data Science Acceleration (DSX) team is responsible for developing scalable data engineering and analytical tools, environments, and workflows that enable efficient, high-quality statistical computing across Product Development Data Sciences and Analytics (PDD). They focus on creating and maintaining next-generation capabilities that support automation of programming workflows, generation of reusable coding macros, and advanced data visualization
Statisticians use their statistical expertise to design, analyse and interpret the results of clinical trials. We are a key member of cross functional teams, working closely with both technical (data management, statistical programming) and non-technical (clinical science, safety science, regulatory) colleagues to ensure the quality, integrity and regulatory compliance of our studies and their results. We also conduct complex exploratory analyses, by applying novel statistical methodologies to answer critical healthcare questions and to fully understand our clinical trial data
Data Stewards ensure that clinical and real-world datasets are documented, accessible, trustworthy, and findable by assisting with provenance tracking, defining metadata, and cataloging datasets. Working across operational, clinical trial, and real-world data, they produce interactive catalogue entries, aligned and standard data dictionaries that enable scientists to locate and reuse data, while ensuring compliance with data privacy and security regulations such as HIPAA and GDPR
The Data Strategy & Analytics Specialist (DSAS) designs and executes data analyses to support decision-making while translating complex scientific and research questions into structured data requirements. They work with multi-modal data spanning clinical trials, operational metrics, and real-world data to produce analysis reports or dashboards alongside mapped technical specifications for clinical use cases
Clinical Pharmacology Data Scientists (CPDS) supports the Quantitative Clinical Pharmacology department by creating ready to use analysis datasets, providing graphical evaluation of the data and conducting exploratory analysis. We work closely with Clinical Pharmacologists to analyse and report data from clinical studies. We also work closely with Pharmacometricians who use modelling and simulation techniques to support the drug development process

Qualification

Required

You must be studying for an undergraduate or integrated masters degree, and be eligible to work in the UK
Applicants must be able to attend an in-person assessment centre on either 25th or 26th November 2026 at Roche's UK office in Welwyn Garden City
Candidates must already hold valid authorisation to work in the UK
Pursuing a degree in Data Science, Life Sciences, or a related field
Strong attention to detail and organizational skills and can adhere to compliance guardrails and departmental procedures
Demonstrate critical thinking and a willingness to learn
An effective communicator, able to work collaboratively and learn to influence others in both technical and non-technical roles
Pursuing a degree in Data Science, Life Sciences, Bioinformatics, Computer Science or a related field
Strong communication skills, with the capability to bridge technical and non-technical teams effectively
Interest in or ability to use digital tools for project/code management (e.g. Github, Jira) and in basic programming (e.g. simple Python or R)
Ability to manage time and keep projects on track
A logical mindset for identifying process improvements and developing practical solutions to everyday problems
Pursuing a degree in Data Science, Life Sciences, or a related field
Have an understanding of or a willingness to learn about Change Management & Communication strategies
Have an understanding of or a willingness to learn about Knowledge Management and how it contributes to core performance and compliance
Have an understanding of or a willingness to learn about Process Improvement: to help identify gaps and propose process enhancements
Pursuing a degree in Mathematics, Data Science, Bioinformatics, Computer Science, Statistics, or a related quantitative or computational field
Good problem solving and logical thinking skills, as well as a keen interest in analytics
A curious mindset with an eagerness to learn about what we do as a business as well as strengthening your technical skills
Able to perform well as part of cross-functional and interdisciplinary development teams under general supervision
Strong communication skills, with the capability to bridge technical and non-technical teams effectively
Ability to manage time and keep projects on track
Pursuing a degree in Mathematics, Data Science, Bioinformatics, Computer Science, Statistics, or a related quantitative field
Knowledge and understanding of basic statistics, with an interest in developing your statistical skills further
Comfortable working as part of teams consisting of both technical and non-technical colleagues
Pursuing a degree in Life Sciences, Pharmacoepidemiology, Data Science, Statistics, Mathematics, or a related quantitative field
Have strong critical thinking and a desire to learn or build on basic programming skills in Python, R, or SQL
Excited to learn about real world and clinical trial data, data modeling, metadata, clinical trial systems, or global data standards and privacy (GDPR/HIPAA) under the guidance of senior specialists
Pursuing a scientific, or data related degree
Have good problem solving and logical thinking skills
Have R programming experience (or other coding language), including data visualisation
Have an interest in how biological systems work
Are able to work independently and as part of a team

Preferred

Knowledge of some programming languages (R, SAS, Python) beneficial
Knowledge and experience programming in R or SAS (among other languages) beneficial
Have some familiarity with Microsoft Office, or Google equivalent