Overview
In this role you lead the Scientific AI Platform efforts within DAx Data Science to deliver scalable AI analyses and data products that accelerate drug discovery. You partner with multidisciplinary teams to operationalize AI solutions and shape the DAx data strategy while collaborating with enterprise IT. You translate scientific needs into impact-driven platforms and mentor cross-functional colleagues. This is a hands-on, strategic role at the intersection of science, engineering, and product delivery, with the chance to influence enterprise AI practices at Novartis.
Pay / Benefits
- comprehensive benefits package (health, life, disability)
- 401(k) with company contribution and match
- vacation, personal days, holidays, leaves
- performance-based cash incentive
- eligibility for annual equity awards
- flexible work arrangements (hybrid in Cambridge)
Responsibilities
- Translate scientific and operational AI needs into decision-enabling solutions
- Design, build, and sustain scalable AI-focused omics pipelines, APIs, and integrated data products
- Scale AI workflows with 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
- Communicate strategy, implementation details and results through internal and external presentations, posters, publications, and technical documentation
Key requirements
- PhD in AI/ML, data science/engineering, computational biology, bioinformatics, computer science/engineering, mathematics, physics, or related discipline with equivalent practical 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 (genomics, transcriptomics), MCP, LLM patterns, biological foundational models, agent orchestration, and deep learning frameworks (e.g. PyTorch) is preferred
- Familiarity with agentic frameworks such as 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 (e.g. agile), including Python, SQL, version control, testing, workflow orchestration, cloud platforms, and data lakes (e.g. Snowflake, Databricks, Palantir Foundry, AWS)
- Experience leading and supporting cross-functionally across diverse science or engineering teams, influencing stakeholders in a matrix organization
- Strong communication, interpersonal, ethical, self-awareness, and customer service skills
- strong communication
- interpersonal skills
- ethical awareness
- Python
- SQL
- version control
Scientific AI Platform Lead, Data Science, Disease Area X in Cambridge employer: Novartis
Novartis is an exceptional employer that fosters a collaborative and inclusive work environment, where passionate individuals come together to drive breakthroughs in precision medicine. With competitive salaries, flexible working arrangements, and robust learning and development opportunities, employees are empowered to grow both personally and professionally while making a meaningful impact on patients' lives. Located in vibrant cities like London, Barcelona, and Dublin, Novartis offers a dynamic workplace that values diversity and encourages innovation.
