Cambridge Hybrid AI Platform Lead - Scientific Data Science

Novartis AG; Cambridge (MA); Hybrid; USD 126,000 - 257,000; Full time

Benefits offered by this job

Health benefits

401(k) with match

Paid time off

Job summary

Novartis in Cambridge, MA, seeks a Scientific AI Platform Lead to build enterprise-grade AI analysis platforms and data products that accelerate drug discovery. The role partners across multidisciplinary teams, operationalizes generative AI, and shapes the DAx AI data strategy, reporting to the Head of Data Science, DAx.

The position requires a PhD or MS with relevant experience, 3+ years in data science/engineering, and production-grade data platforms expertise.

Qualifications

• PhD in AI/ML or related field with equivalent practical experience; MS degree with 5+ years considered.
• 3+ years hands-on experience in scientific data science or engineering, AI/ML in biopharma or tech.
• Experience building and operating production-grade multimodal data platforms for scientific analysis.

Responsibilities

• Translate scientific and operational AI needs into impactful, decision-enabling solutions.
• Design, build, and sustain scalable AI-focused omics pipelines, APIs, and data products.
• Scale AI workflows using reproducible, secure, and FAIR data practices.
• Mentor wet lab scientists, data scientists, engineers, and cross-functional teams.
• Provide oversight of external vendors and communicate strategy and results.

Skills

AI/ML

Data Science

Python

Cloud platforms

Leadership

Communication

Education

PhD or MS with 5+ years experience

Tools

Snowflake

Databricks

Palantir Foundry

AWS

Job description

Novartis in Cambridge, MA, seeks a Scientific AI Platform Lead to build enterprise-grade AI analysis platforms and data products that accelerate drug discovery. The role partners across multidisciplinary teams, operationalizes generative AI, and shapes the DAx AI data strategy, reporting to the Head of Data Science, DAx.

The position requires a PhD or MS with relevant experience, 3+ years in data science/engineering, and production-grade data platforms expertise.