Executive Director - Data Management, Analytics, AI & Architecture

Regeneron is a leading biotechnology company built on a simple but powerful mission: to use the power of science to bring new medicines to patients, over and over again. Founded and led by physician-scientists, we’ve turned that mission into one of the industry’s most productive pipelines, nearly all of it homegrown in our own laboratories, powered by proprietary technologies like our VelociSuite platform. From Dupixent and EYLEA to a rapidly expanding portfolio across oncology, cardiovascular and metabolic disease, neuroscience, and rare disease, our science is reaching millions of patients worldwide, and we’re just getting started.

As we invest billions in new manufacturing capacity, expand our global footprint, and build the next generation of digital and technology capabilities to match the scale of our ambition, Regeneron offers a rare combination: the resources and reach of an industry leader, paired with the energy, curiosity, and relentless focus on invention of a company still writing its next chapter. This is a place where technology doesn’t just support the business, it accelerates the science that changes patients’ lives.

This role will sit on-site in our Sleepy Hollow, NY offices 4 days per week. Role Description The Executive Director of Data Management, Analytics, and Architecture will lead the strategy for commercial and G&A data capabilities at Regeneron, transforming enterprise data into trusted insights that drive business performance and operational excellence. This role partners closely with Digital & Technology leaders and senior executives to establish scalable data architecture, analytics, and governance standards that serve as a model across the organization.The position has significant influence over how data, AI, and analytics are structured, managed, and leveraged to support commercial and operational decision-making. The leader also serves as the primary executive spokesperson for data management, analytics, and architecture across Commercial and G&A functions, including Finance, HR, Procurement, Legal, Compliance, and other corporate departments.

What You’ll Lead

• Own and execute the multi-year data management, analytics, AI, and enterprise data architecture strategy for Commercial and G&A functions, aligning investments with corporate objectives.
• Lead and develop a high-performing team of data management, analytics, and architecture professionals, building organizational capability and delivery excellence.
• Deliver trusted data platforms, analytics products, and self-service capabilities that empower business leaders across Commercial, Finance, HR, and other G&A functions.
• Establish enterprise-wide data governance, stewardship, quality, lifecycle management, and master data standards to improve trust, consistency, and interoperability.
• Modernize and simplify the data ecosystem through scalable cloud platforms, integration strategies, architecture standards, and executive reporting capabilities.
• Advance AI, machine learning, automation, and responsible AI practices by identifying high-value use cases, managing risk, and ensuring regulatory compliance.
• Drive measurable business outcomes through improved data quality, analytics adoption, automation, operational efficiency, productivity, and process standardization across global teams.
• Oversee vendor partnerships, data security, architecture governance, and value realization, ensuring strategic investments deliver measurable business impact and long-term organizational value.

What You Bring

• BS/BA in Computer Science, Data Science, Information Systems, or a related field required; MS. PhD or MBA preferred.
• 17+ years of progressive leadership in data management, data architecture, analytics, or business intelligence, including enterprise-scale programs; experience in life sciences, biotechnology, or another regulated industry is a plus.
• Deep command of modern data management, analytics, and enterprise architecture capabilities (platform-agnostic, e.g., BI, cloud data platforms, data governance, data modeling, master data management).
• Experience establishing enterprise data governance frameworks and reference architecture standards that scale across multiple business domains.
• Strong understanding of AI, machine learning, and agentic AI concepts, including model risk, responsible AI practices, and the operational discipline, such as monitoring, validation, and lifecycle management, n…