Director, Data Science - AI Evidence Extraction

Description

The company is the company, and this role sits in the Research and Development Data, Data Science, and AI (DDSAI) team.

The Director will lead the design, development and rollout of AI-enabled tools, such as agentic workflows, for extracting, curating and quantitatively synthesizing scientific evidence to support clinical development in Neuroscience R&D.

You will work closely with clinical, statistical, regulatory, scientific and data colleagues to turn priority evidence needs into scalable tools and reusable data assets, improving how literature and other sources are found, structured, assessed and analyzed.

You will be a hands-on technical leader who sets direction, guides cross-functional delivery, and builds and validates strong evidence workflows.

You will define fit-for-purpose data models, provenance and quality standards, evaluation and human-review practices, and rigorous analytical methods, while keeping work aligned with enterprise platforms, responsible AI expectations and data-use rules.

Success depends on partnering across functions to build workflows, drive adoption, and communicate uncertainty, tradeoffs and measurable value for clinical development decisions.

Most AI systems give answers that are soon forgotten. This role builds a curated evidence asset with clear provenance, so each later analysis is faster, cheaper and more reliable. The Director chooses evidence domains, ensures compliant data use, and sets standards other programs can reuse.

At twelve months, success means Neuroscience analysts start meta-analyses by querying this evidence store, reviewers can trace pooled values to cited sources unaided, and other therapeutic areas want to adopt the capability.

Responsibilities

• Set the strategy, roadmap, priorities and value measures for scientific evidence data capabilities in Neuroscience.
• Build and deploy scalable AI-enabled workflows, such as AI agents, for evidence identification, extraction, curation and analysis.
• Own delivery, investment decisions and outcomes for AI-based scientific evidence extraction.
• Work with data teams to create fit-for-purpose data models and databases, provenance, quality controls and reusable evidence assets.
• Define validation, evaluation, human-review and responsible AI practices.
• Develop rigorous analysis workflows and quantify their limitations, including uncertainty.
• Partner with clinical, statistical, regulatory, scientific, legal and technology stakeholders.
• Help shape shared platform capabilities and keep them aligned with architecture, governance and data-use requirements.
• Guide multidisciplinary delivery, maintain strong engineering practices, and mentor cross-functional contributors.
• Explain priorities, tradeoffs, risks, progress and impact to senior stakeholders.

Requirements

• PhD in a relevant quantitative, clinical or life-science field, or an MS with additional relevant experience.
• 8+ years in pharmaceutical, biotech or healthcare analytics, including setting technical direction.
• Hands-on experience with systematic reviews, meta-analysis or quantitative evidence synthesis.
• Experience with data modeling, scientific data curation, provenance and quality control.
• Recent experience building and deploying scalable AI, NLP or generative AI solutions.
• Strong proficiency in Python and/or R, with sound software engineering practices.
• Understanding of evaluation, validation, uncertainty and human-in-the-loop review.
• Ability to assess scientific evidence and make well-reasoned technical tradeoffs.
• Proven cross-functional leadership and influence without relying on managerial authority.
• Strong communication with technical, scientific and senior non-technical audiences.
• Experience working within shared platforms, architecture standards and governance frameworks.
• Preferred: exposure to regulated environments, multimodal document extraction, AI governance and responsible AI.
• The role is based at one of the US sites: Raritan, NJ; Titusville, NJ; Cambridge, MA; or Spring House, PA. Travel may be required as needed.
• Preferred skills include: Advanced Analytics, Budget Management, Compliance Management, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Developing Others, Digital Fluency, Inclusive Leadership, Leadership, Program Management, Strategic Thinking, Succession Planning.

Conditions

Hybrid work model, with the location set at one of the four US sites listed above.

Base pay range is $164,000 to $282,900 for candidates hired in the United States. Candidates hired outside the US receive pay and benefits set by their local market.

The role is eligible for a performance-based annual cash bonus under the applicable plan, awarded at the company's discretion.

The company is committed to an inclusive interview process and offers accommodation on request for candidates with disabilities.

Benefits

• Medical, dental, vision, life insurance, short- and long-term disability, business accident insurance and group legal insurance.
• Eligibility for the consolidated retirement plan (pension) and the savings plan (401(k)).
• Vacation of up to 120 hours per calendar year.
• Sick time of up to 40 hours per calendar year.
• Holiday pay, including floating holidays, of up to 13 days per calendar year.
• Work, personal and family time of up to 40 hours per calendar year.