Statistics (Biostatistics) Graduate Rotational Programme, UK, 2026

Real World Data, Measurement & Analytics (RWDMA) 

Use real-world data to answer questions that improve patient outcomes 
Real-world evidence is increasingly essential to how healthcare and regulatory decisions are made. Apply statistical thinking and causal inference to real world evidence and measurement challenges, helping translate healthcare data into decision ready insights. Rotations may include study design and analysis using observational data sources, endpoint/measurement strategies including digital and patient reported outcomes, and transparent, reproducible analytics to support evidence generation. 

(Where relevant, rotations may also include work with Statistics & Data Science Innovation Hub -SDSIH – within Development Sciences, focusing on scalable analytics, innovation, and methodological development) 

Vaccines, Infectious Diseases & HIV Statistics 

Shape evidence in diseases where speed and prevention both matter 
In vaccines, infectious diseases and HIV, evidence generation demands both scientific depth and operational excellence. Support evidence generation in areas where speed, rigour and clear communication of uncertainty are critical. Rotations may span clinical study design and analysis, innovative approaches to trial designs and questions, and crossfunctional collaboration to deliver highquality evidence that informs development and external discussions. 

Respiratory, Immunology & Inflammation (RI&I) Statistics   

Advance medicines through smarter trial design and stronger inference 

In respiratory, immunology and inflammation, development decisions often hinge on complex endpoints, heterogeneous patient populations, and rigorous interpretation. This rotation offers supporting studies and programmes where statistical leadership optimises designs, strengthens inference, and accelerates learning; decision focused statistics that improves study focused statistics that improves trial effectiveness and supports robust portfolio decisions. 

Oncology Statistics  

Generate robust evidence in complex oncology development programmes  

Oncology evidence generation often requires careful design choices, clear estimands, and rigorous interpretation across diverse settings (for example blood cancers, solid tumours, and immuno-oncology). Rotations may include clinical study design and analysis, benefit–risk and uncertainty communication, and collaboration across disciplines to inform high-impact development decisions. 

What will you do?  

• Contribute to study delivery under supervision, supporting lead statisticians on defined work packages and agreed timelines.  

• Provide statistical input to the design, analysis, reporting and interpretation of studies, including drafting sections of analysis plans and key documents with guidance.  

• Perform statistical analyses and produce clear outputs using appropriate tools, applying reproducible practices and quality checks to own work.  

• Communicate progress, results and recommendations clearly to technical and non-technical colleagues, adapting messages to the audience and incorporating feedback.  

• Build and maintain effective working relationships within multi-disciplinary teams, collaborating with internal partners and (where appropriate) supporting external interactions under guidance. 

• Contribute to innovation and continuous improvement by exploring new approaches (e.g., modelling, simulation, GenAI, ML, and other modern methods) where appropriate and with support, sharing learnings with the team.  

• Participate in peer review and team discussions, helping strengthen consistency, rigour and good practice across deliverables.  

• Gain experience across the end-to-end development lifecycle through rotations (from early development through registration and lifecycle support), building breadth and confidence over time.  

What are we looking for?  

• MSc degree from an accredited college/university in statistics, with a strong biostatistics or medical statistics focus. Course completion by September 2026. 

• Using statistical software and coding for analysis; knowledge & experience with R is essential. E.g. computational statistics modules. 

• Practical and technical understanding of statistical inference, Bayesian methodology, modelling, and motivation to apply methods to real development questions.  

• Ability to deliver accurate, high-quality work with strong attention to detail, documentation and data integrity.  

• Clear written and verbal communication in English, including ability to explain statistical ideas in plain language and keep supervisors informed of progress and challenges.  

• Collaborative mindset and evidence of working effectively in teams and proactively seeking input when needed. 

• Strong organisation, time management and prioritisation skills; ability to manage tasks to agreed timelines.  

• Learning agility, resilience and a growth mindset - openness to feedback and commitment to building capability in technical skills and critical business skills across rotations.  

What do we offer you?  

• A competitive salary, with an annual bonus based on company performance.   

• Relocation Allowance