Senior Computational & Applied AI Scientist; Data)

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A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.

In Roche's Research and Early Development organisations, we make transformative medicines for patients in order to tackle some of the world’s toughest unmet healthcare needs. We are united by our mission to transform science into medicines. Together, we create a culture defined by curiosity, responsibility and humility, where our talented people are empowered and inspired to bring forward extraordinary life-changing innovation at speed.

The Computational Sciences Centre of Excellence is a global organisation enabling Roche’s Research and Early Development units (pRED and gRED) to become more data-driven, more digitally adept and better prepared for the challenges of the future. Within the Computational Sciences Centre of Excellence, Computational Medicine focuses on developing and applying innovative data analysis solutions to support clinical development, furthering our understanding of disease, disease progression, and individual patient’s response to treatment by having access to the largest Pharma R&D datasets in the world.

In partnership with our scientists across pRED and gRED, we create better medicines by augmenting every part of R&D through our data-driven culture.

This position will combine advanced real-world data (RWD) science with generative AI, AI agents, and agentic workflows to develop new analytical capabilities for drug development. You will play a key scientific and technical role within the Real World Data Insights team in Computational Medicine.

You will design and execute high-impact RWD analyses using data such as electronic health records (EHR), claims, registries, and linked clinical or molecular datasets, generating insights into disease, patient populations, biomarkers, and treatment outcomes.

In parallel, you will design and build AI-enabled tools and agentic workflows that transform how RWD analyses are performed. This includes developing reusable analytical components, enabling models and agents to interact with data and tools, automating parts of scientific workflows, and creating scalable solutions that can be adopted across projects and teams.

The role sits at the intersection of RWD science, data science, AI, and software engineering. You will work closely with scientists, data engineers, and computational experts to ensure that both analytical methods and AI-enabled solutions are scientifically robust, technically sound, and useful in practice.

As part of the Computational Biology and Medicine department, you will contribute to broader scientific and technical initiatives and help shape new ways of working with complex healthcare data through AI-enabled approaches.

• Design and execute analyses of real-world healthcare data to support biological, translational, and clinical questions.
• Design, build, and evaluate agentic workflows that enable models to use tools, access data, execute analytical tasks, and support scientific…