Principal real world data scientist

The Opportunity

This position will focus on delivering world‑leading real‑world data (RWD) analytical capabilities at scale. You will play a senior scientific role within the Real World Data Insights team in Computational Medicine. Together with other real‑world data experts and collaboration partners, you will lead the design and execution of complex, high‑impact RWD studies, improving our understanding of disease biology, informing biomarker strategies and generating actionable insights into patient populations and treatment outcome prediction. You will drive the integration of diverse real‑world data sources (e.g., EHR, claims, registries, and linked datasets) and apply advanced analytical approaches to inform clinical development decisions. You will influence and optimise study designs, patient eligibility criteria, and endpoint strategies, ensuring that RWD is effectively leveraged across the drug development lifecycle. You will operate as a trusted strategic partner to senior stakeholders, translating complex analytical findings into impactful decisions. As part of the Computational Biology and Medicine department, you will contribute to the broader scientific and technical strategy, drawing on global expertise and driving best practices in RWD analysis. You will also play a key role in mentoring and developing talent, and establishing methodological standards and scalable analytical solutions.

In this role you will:

• Strategic Decision Support: Lead the design and execution of complex data analyses to guide investment and clinical decisions across early‑phase programmes.
• Methodological Excellence: Ensure all RWD outputs are reproducible, statistically rigorous, and built using scalable, reusable analytical frameworks.
• Innovative Trial Design: Utilize RWD to optimise Phase I/II settings through cohort definition, endpoint exploration, and the development of external control arms.
• Precision Medicine Integration: Combine RWD with biomarker and omics data to map patient trajectories and enable targeted, personalised treatment approaches.
• Team Mentorship: Act as a technical and scientific lead to develop junior talent and foster a high‑performing, collaborative research culture.
• Cross‑Functional Partnership: Serve as a trusted scientific liaison between data functions and clinical stakeholders to align evidence generation with portfolio priorities.

Who you are:

• A PhD in Epidemiology, Biostatistics, Data Science, Bioinformatics, or a related field with 3+ years of experience applying real‑world data analysis in pharmaceutical R&D or healthcare is required.
• Deep, hands‑on expertise in real‑world data analysis, with a strong focus on delivering insightful outcomes in early development applications, and strong understanding of disease biology and clinical development is required.
• Proven ability to connect data insights to decision‑making is required.
• Solid programming skills in R and/or Python, advanced AI/ML literacy, applied biostatistics, and strong expertise in data integration and visualisation is required.
• Deep familiarity with real‑world data sources (e.g., EHR, claims, registries) and their strengths, limitations, and appropriate use in different research contexts is required.
• Demonstrable evidence of contributing to high‑performing and multidisciplinary teams, and experience mentoring and developing others is preferred.
• Strong communication skills, with the ability to translate complex analyses into clear, actionable insights for diverse audiences is preferred.
• Demonstrated ability to build collaborative, trust‑based relationships across functions and within the broader corporate ecosystem is preferred.