Scientific AI Platform Lead, Data Science, Disease Area X

Salary Range: CHF102,200.00 - CHF189,800.00   Job Description Summary The Scientific AI Platform Lead will join the Disease Area X (DAx) Data Science team at Novartis to build enterprise-grade, AI analysis platforms and data products to accelerate drug discovery. This role will lead and partner on multidisciplinary project teams, operationalize generative and agentic AI solutions, shape DAx AI data strategy, and collaborate with enterprise IT teams. This role reports to the Head of Data Science, DAx.   Job Description Internal job title:  Senior Expert I/II, Data Science   Position Location : Basel, Switzerland (Hybrid) ** This role is based in Basel, Switzerland. Novartis is unable to offer relocation support for this role: please only apply if this location is accessible for you.    Job description Summary:   The Scientific AI Platform Lead will join the Disease Area X (DAx) Data Science team at Novartis to build enterprise-grade, AI analysis platforms and data products to accelerate drug discovery. This role will lead and partner on multidisciplinary project teams, operationalize generative and agentic AI solutions, shape DAx AI data strategy, and collaborate with enterprise IT teams. This role reports to the Head of Data Science, DAx.   Responsibilities: • Translate scientific and operational AI needs into impactful, decision-enabling solutions. • Hands-on design, build, and sustain scalable AI-focused omics pipelines, APIs, and integrated data products. • Scale AI workflows using reproducible, transparent, secure, and FAIR data practices. • Prioritize resources against evolving research needs. • Establish rigorous project evaluation, deployment, lifecycle, and governance practices. • Mentor, train and coach wet lab scientists, data scientists, engineers, and cross-functional teams. • Provide oversight and onboarding of external vendors and service providers. • Effectively communicate strategy, implementation details and results through internal and external presentations, posters, publications, and technical documentation.   Requirements :                                                         • PhD in AI/ML, data science/engineering, computational biology, bioinformatics, computer science/engineering, mathematics, physics, or a related discipline with equivalent practical experience. • We will also consider qualified MS degree applicants with 5+ years of relevant post-graduate experience. • 3+ years of hands-on experience in scientific data science or engineering, AI/ML, computational research within biopharma and/or technology industry • Experience building and operating production-grade multimodal data platforms for scientific analysis: omics data, data modeling, patient metadata, lineage, access controls, and reproducible workflows. • Experience with omics analysis pipelines (i.e. genomics, transcriptomics), MCP, LLM patterns, biological foundational models, agent orchestration, and deep learning frameworks (i.e. Pytorch) is preferred. • Familiarity with current agentic frameworks such Claude Science, Biomni, Gemini or other open-source co-scientist platforms. • Demonstrated record of scientific or technical impact through publications, conference proceedings, open-source contributions, patents, or deployed data products. • Deep practical experience in software or data engineering (i.e. agile), including Python, SQL, version control, testing, workflow orchestration, cloud platforms, and data lakes (i.e. Snowflake, Databricks, Palantir Foundry, AWS). • Experience leading and supporting cross-functionally across diverse science or engineering teams, influencing key stakeholders across a matrix organization. • Strong communication, interpersonal, ethical, self-awareness, and customer service skills.