Novartis
Scientific AI Platform Lead, Data Science, Disease Area X
$126K–$257K
Cambridge (USA) · Full-time · Posted Oct 17, 2026
- Experience
- 3+ years of hands-on relevant experience; alternatively, qualified MS applicants with 5+ years of relevant post-graduate experience.
- Education
- PhD in AI/ML, data science/engineering, computational biology, bioinformatics, computer science/engineering, mathematics, physics, or a related discipline with equivalent practical experience; qualified MS applicants also considered with 5+ years of relevant post-graduate experience.
About the job
Builds and leads scalable scientific AI platforms and data products to accelerate drug discovery, while shaping AI strategy and operationalizing AI solutions.
What you'll do
- Design, build, and sustain AI-focused omics pipelines, APIs, and integrated data products.
- Establish scalable AI workflows and practices for evaluation, deployment, lifecycle management, and governance.
- Lead and mentor multidisciplinary teams, coordinate vendors, and communicate strategy and results.
What they ask for
- PhD in a related discipline with equivalent practical experience, or a qualified MS applicant with 5+ years of relevant post-graduate experience.
- 3+ years of hands-on experience in scientific data science or engineering, AI/ML, or computational research within biopharma and/or technology.
- Experience building and operating production-grade multimodal data platforms for scientific analysis.
- Practical software or data engineering experience, including Python, SQL, version control, testing, workflow orchestration, cloud platforms, and data lakes.
Nice to have
- Experience with omics pipelines, MCP, LLM patterns, biological foundational models, agent orchestration, and deep learning frameworks such as Pytorch.
- Familiarity with agentic frameworks such Claude Science, Biomni, Gemini, or other open-source co-scientist platforms.
Pay
$126,000 and $234,000 USD annually (base salary); $138,600 and $257,400 USD annually (base salary)
Tools
Python, SQL, Pytorch, MCP, Claude Science, Biomni, Gemini, Snowflake
AI focus
Build and operate scientific AI analysis platforms and data products for drug discovery; operationalize generative and agentic AI solutions and shape AI data strategy.
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