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

Apply Now

Data Science Industrial Placement Student

F. Hoffmann-La Roche AG
Welwyn Garden City
2 days ago
Create job alert

The PDD Department in Welwyn Garden City is seeking industrial placement students starting in July 2026 for 13 months to support the advancement of medicines. Successful candidates will be evaluated for multiple roles across the department, each requiring a diverse range of skills. These roles offer opportunities to leverage your expertise or interest in areas such as:Role: Biostatisticians use statistical methods to design and analyse the data collected in our clinical trials. We often collaborate with clinical scientists to interpret results, and work closely with other members of data science eg. Data Management and Statistical Programming, to ensure the quality and integrity of study data. We also conduct exploratory analyses, trialling new or alternative statistical methods to better understand our data, and inform decision making.Skills: Knowledge and understanding of basic statistics; programming skills (R, SAS or other coding languages) are beneficial.* Role: Analytical Data Scientist (ADS) - We 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.* Skills: Programming skills (R, SAS or anything else) are beneficial; ability to explain complex concepts to non-technical audiences; growth mindset; innovationRole: Study Data Manager (SDM) - We are responsible for the collection, delivery and quality of data in standardized, quality clinical trial databases, in readiness for analysis by Statistical Programming and Biostatistics. We operate in a cross functional team and in partnership with external business partners utilizing a variety of data surveillance tools with disease area knowledgeSkills: Project Management - Programming experience is not essentialRole: Data Acquisition Specialist (DAS)- We are responsible for acquiring external data, eg. MRI images, spirometry, ECGs, biomarker data, in a standardized format for inclusion with the database captured clinical trial data. We operate in a cross functional team and in partnership with external vendors, utilizing a variety of data collection tools and scientific knowledge.Skills: Programming experience is not essentialRole: Technical Excellence - We accelerate data delivery (acquisition, access & review) by innovative, sustainable and scalable solutions, including automation and AI/MLSkills; programming skills (R, python or anything else); ability to explain complex concepts to non-technical audiences; any of Git; AI/ML; data visualisation (e.g. graphs); software development; CI/CD; database management/administration (e.g. SQL, AWS) are beneficial but not essential.Role: The Business Strategy & Operations team ensures regulatory alignment, quality, and compliance, manages vendor relationships, oversees data monitoring and healthcare professional interactions, drives efficiency through automation and knowledge management, and facilitates secure, transparent data sharing in compliance with data protection laws. Project management & strategic planning skills would be useful. Role: To support the conduct of Quantitative Clinical Pharmacology activities by creating ready to use analysis datasets, providing graphical evaluation of the data and conducting exploratory analysis. Skills: R programming experience (or other coding language); familiarity with Microsoft Office, or Google equivalent; data visualisation (e.g. graphs); an interest in how biological systems work.Role: We provide expertise and strategic oversight in the conceptualisation, design, conduct, analysis and interpretation of real world data studies, as well as secondary use and standardisation of both clinical trial data and trial operational data, for the development of access to Roche’s medicines. Key skills: Communication (written and verbal); problem solving; collaboration and interpersonal skills; time management; analytical thinking; attention to detail* An undergraduate in their second year of their Bachelor's/second or third year of their Integrated Masters Degree* Currently undertaking a relevant data-oriented subject (e.g. Biological/ Biomedical Sciences, Neuroscience, Mathematics, Statistics, Data Science, Bioengineering, Computer Science etc.)* Interested in healthcare, data science and drug development - a passion for healthcare and enthusiasm are vital.* Experience or has knowledge in data handling and analysis techniques. Familiarity with programming languages like R, Python or SAS is advantageous for certain roles but not mandatory.* Values and contributes to a supportive and inclusive collaborative working environment.* Has a good understanding of their own strengths and areas for development.
#J-18808-Ljbffr

Related Jobs

View all jobs

Data Science Industrial Placement Student

Data Science Industrial Placement Student

Data Science Industrial Placement Student

2026 Digital and Data Analyst Industrial Placement - Warwick

2026 Digital and Data Analyst Industrial Placement

Physics with Data Science MPhys Physics with Data Science MPhys, 4-5 years

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.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.