Senior Computational & Applied AI Scientist (Real-World Data))

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

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.

The Opportunity

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 decision-making while maintaining scientific rigor, traceability, and human oversight.

● Apply machine learning, large language models, retrieval- and tool-augmented approaches, and other modern AI methods to healthcare and biomedical data.

● Integrate RWD with clinical, biomarker, genomic, or other molecular data to generate deeper insights into disease and patient trajectories.

● Collaborate with scientific, clinical, data, and engineering teams to translate analytical needs into fit-for-purpose scientific and technical solutions.

Who you are

●A PhD in Epidemiology, Biostatistics, Data Science, Bioinformatics, Computer Science, Computational Biology, or a related quantitative field, with 2+ years of relevant professional experience in pharmaceutical or biotech R&D, drug development, or a closely related setting.

● Hands-on experience working with real-world healthcare data such as EHR, claims, registries, or linked clinical datasets, with a strong understanding of data quality, bias, limitations, and fit-for-purpose use.

● Experience applying statistical and machine-learning methods to healthcare, biomedical, or life-science data, with the ability to assess methodological assumptions, performance, and limitations.

● Strong scientific and analytical judgment, and the ability to collaborate and communicate effectively across data science, engineering, and biomedical teams.

● A growth mindset with a passion for continuous learning, innovation, and adopting emerging computational technologies, including Generative AI and Agentic AI approaches to scientific discovery.

● Hands-on experience designing and building production-oriented AI agents or agentic systems, including capabilities such as tool/function calling, retrieval, structured outputs, routing or orchestration, and multi-step or multi-agent workflows.

● Experience evaluating and improving AI-enabled systems, including testing performance, monitoring behavior, adding safeguards, and incorporating human review where appropriate.

● Experience with software-engineering and production AI practices, including version control, automated testing, APIs, containers, cloud platforms, workflow orchestration, CI/CD, and deployment or operation of ML/AI applications.

● Experience integrating RWD with biomarkers, genomics, clinical trial data, or other multimodal datasets.

● Experience with advanced observational and causal-inference methods, such as longitudinal methods or target-trial emulation, and/or experience with clinical study design.

Unwavering focus, collaborative teamwork, and exceptional delivery are key behaviors that drive our mission of doing now what patients need next. Together, we can be transformative.

If you are passionate about contributing to a committed team and have the dedication to partnership and innovation, Roche is the place for you! Every role at Roche plays a part in making a difference in patients’ lives. Apply now and join us in making an impact!

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Global Grade: SE6.

Please note that the global grade displayed is a target global grade for the role and the actual global grade offered to a candidate may vary depending on several factors - including scope and breadth of the role. For further information relating to global grading in Roche please visit the global grading gSite. Local regulations continue to apply.

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.

Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.