Join Roche as a Senior Computational & Applied AI Scientist to advance real-world data science and generative AI in drug development. Lead the design and execution of complex RWD analyses and AI-enabled workflows, collaborating with multidisciplinary teams. This role is ideal for candidates with a PhD and significant experience in pharmaceutical or biotech R&D.
Tasks
- 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.
- Contribute to broader scientific and technical initiatives within the Computational Biology and Medicine department and help shape new ways of working with complex healthcare data through AI-enabled approaches.
Requirements
- 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.
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Über uns
Das Team
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 and digitally adept. Within this, Computational Medicine develops and applies innovative data analysis solutions to support clinical development, furthering understanding of disease, progression, and patient response by accessing the largest Pharma R&D datasets in the world. The Real World Data Insights team in Computational Medicine works closely with scientists, data engineers, and computational experts to ensure analytical methods and AI-enabled solutions are scientifically robust and technically sound.