Scientist – Assay Data, AI & Workflows

About the role

Roche's Pharmaceutical Research and Early Development (pRED) organization is looking for a versatile Scientist to act as its primary operational and computational architect, embedded in the wet-lab scientific community. The role bridges laboratory work and digital infrastructure, shaping how active learning loops could redesign small-molecule assay development for screening and profiling, while championing platform adoption and training bench scientists.

Key responsibilities

• Lead the co-development, rollout and continuous training of end-to-end assay development and screening laboratory information management systems (LIMS), ensuring complete, traceable data trails and digital twins.
• Design and integrate Agentic AI tools and Design of Experiments (DoE) frameworks.
• Build and adjust pipelines that connect raw instrument outputs directly with databases, achieving robust FAIR (Findable, Accessible, Interoperable, Reusable) data standards.
• Coordinate user onboarding, train bench scientists and promote platform adoption across the scientific community.
• Accelerate assay design and execution times, lower processing error rates and resolve operational bottlenecks.

Required profile

• Ph.D. or M.S. in Computational Biology, Scientific Informatics, Bioinformatics, Biology/Biochemistry with a strong computational focus, or a related quantitative discipline.
• Solid experience in cellular, biochemical or biophysical systems and familiarity with FAIR data management standards.
• Proven experience with laboratory informatics environments (e.g., LIMS or electronic lab notebooks) alongside wet-lab work, including Design of Experiments.
• Collaborative communicator with a customer-centric mindset, able to train cross-functional users and manage stakeholder relationships.

Required skills

• Strong programming, including building or maintaining databases and automating data extraction.
• ML/LLM API integration.