Scientific AI Platform Lead, Data Science, Disease Area X

Description

You will join the Disease Area X (DAx) Data Science team at the company to build enterprise-grade AI analysis platforms and data products that speed up drug discovery.

You will lead projects that span several disciplines, put generative and agentic AI into production, set the AI data strategy for DAx, and work with enterprise IT teams.

You report to the Head of Data Science, DAx. The internal title is Senior Expert I/II, Data Science.

Responsibilities

• Turn scientific and operational AI needs into solutions that help people make decisions.
• Design, build and maintain scalable omics pipelines, APIs and integrated data products, writing hands-on code.
• Scale AI workflows so they are reproducible, transparent and secure, and follow FAIR data principles.
• Decide how to allocate resources as research priorities change.
• Set up rigorous practices for evaluating, deploying, managing across the lifecycle, and governing projects.
• Mentor, train and coach wet lab scientists, data scientists, engineers and other cross-functional colleagues.
• Oversee external vendors and service providers, including onboarding them.
• Explain strategy, implementation and results in internal and external presentations, posters, publications and technical documents.

Requirements

• A PhD in AI/ML, data science or engineering, computational biology, bioinformatics, computer science or engineering, mathematics, physics, or a related field, or equivalent practical experience.
• Alternatively, an MS degree plus 5+ years of relevant experience after the degree.
• 3+ years of hands-on work in scientific data science or engineering, AI/ML, or computational research in biopharma and/or technology.
• Experience building and running production multimodal data platforms for scientific analysis, covering omics data, data modeling, patient metadata, lineage, access control and reproducible workflows.
• Preferred: experience with omics pipelines (for example genomics and transcriptomics), MCP, LLM patterns, biological foundation models, agent orchestration, and deep learning frameworks such as PyTorch.
• Familiarity with current agentic frameworks such as Claude Science, Biomni, Gemini, or other open-source co-scientist platforms.
• A proven record of scientific or technical impact through publications, conference proceedings, open-source work, patents, or deployed data products.
• Deep practical experience in software or data engineering, including agile methods, Python, SQL, version control, testing, workflow orchestration, cloud platforms, and data lakes such as Snowflake, Databricks, Palantir Foundry or AWS.
• Experience leading and working across diverse science or engineering teams, and influencing key stakeholders in a matrix organization.
• Strong communication, interpersonal, ethical and customer service skills, along with self-awareness.
• Skills in artificial intelligence, biostatistics, change management, a curious mindset, data governance, data literacy, data quality, data science, data visualization, deep learning, graph algorithms, learning agility, machine learning, machine learning algorithms, Python, stakeholder engagement, statistical analysis, and time series analysis.

Conditions

The role is based in Cambridge, MA, on a hybrid schedule.

The company cannot offer relocation support, so apply only if you can work from Cambridge, MA.

Senior Expert I, Data Science pays $126,000 to $234,000 USD per year. Senior Expert II, Data Science pays $138,600 to $257,400 USD per year.

The final offer depends on factors such as skills and experience, and pay is reviewed periodically after you join. The company may change the published range based on company and market conditions.

Pay includes a performance-based cash incentive and, depending on level, eligibility for annual equity awards.

Benefits

• US-based eligible employees receive a full benefits package with health, life and disability coverage, and a 401(k) with company contribution and match, plus other benefits.
• Generous time off includes vacation, personal days, holidays and other leaves.