Senior Director, Advanced Analytics and Data Science

Role Overview

The Senior Director, Advanced Analytics and Data Science will be part of the Advanced Analytics Center of Excellence (CoE), sitting within Global Insights and Analytics, and will lead the strategy, development, and scaling of advanced analytics and AI-enabled solutions that enable data-driven decision-making across Commercial, Medical Affairs, and Clinical Operations. This leader will translate complex data into actionable insights across the patient journey, healthcare provider engagement, scientific exchange, clinical trial acceleration, and omnichannel customer experiences, while serving as an AI leader who helps the organization responsibly identify, prioritize, and scale opportunities to improve performance and deliver meaningful value to patients, healthcare professionals, and stakeholders.

This is a highly collaborative leadership role that partners closely with Commercial, Medical Affairs, Clinical Operations, Marketing, Sales, Market Access, Medical Excellence, Clinical Development, IT, Data Engineering, Legal, Compliance, and external partners to build scalable analytics and AI capabilities, strengthen data and model governance, and embed insights into day-to-day decision-making.

Key Responsibilities

Analytics Strategy and Capability Development

• Define and lead the advanced analytics capability roadmap, aligning analytics investments with priorities across Commercial, Medical Affairs, and Clinical Operations and measurable enterprise outcomes.

• Develop patient journey and evidence-oriented analytics using longitudinal healthcare data, claims, prescription, specialty pharmacy, EHR, clinical trial, real-world data, and other relevant data sources to identify key moments of intervention, access barriers, adherence challenges, scientific insights, and CT acceleration.

• Design and scale analytics solutions that support omnichannel engagement, customer segmentation, campaign measurement, field effectiveness, medical engagement, and CT acceleration.

• Lead the development and deployment of predictive models, machine learning capabilities, next-best-action solutions, and decision-support tools that enable more personalized, evidence-based, and effective engagement and operational planning.

• Shape and evangelize the organization’s AI strategy for analytics, including practical use cases for generative AI, agentic AI, natural language interfaces, intelligent automation, and decision intelligence across Commercial, Medical Affairs, and Clinical Operations.

Cross-Functional Leadership and Business Partnership

• Serve as a strategic partner to Commercial, Medical Affairs, and Clinical Operations leaders by translating business, scientific, and operational questions into analytical approaches, data requirements, and actionable recommendations.

• Bridge business, medical, clinical, and technical teams by converting analytics outputs into clear narratives, decision frameworks, and implementation plans for stakeholders at all levels.

• Partner with IT, Data Engineering, Legal, Privacy, Compliance, Medical, and Clinical Operations stakeholders to ensure analytics products, AI/ML models, and data practices meet applicable privacy, security, scientific, regulatory, and ethical expectations.

• Champion responsible AI practices by promoting transparency, model explainability, bias awareness, human oversight, fit-for-purpose validation, and appropriate governance for AI-enabled decision support.

• Collaborate with internal teams and external vendors to deliver high-quality analytics solutions efficiently and with strong adoption across the organization.

Team Leadership and Organizational Enablement

• Serve as a thought leader in driving the creation, responsible adoption, and continuous evolution of advanced analytics, AI, and machine learning capabilities across Commercial, Medical Affairs, and Clinical Operations teams.

• Lead, mentor, and develop a high-performing team of data scientists, analysts, and analytics partners, while managing external resources as needed.

• Establish practical operating models, standards, and best practices that improve analytics quality, scalability, and speed to insight.

• Promote a culture of data-driven decision-making by increasing analytics literacy, building stakeholder confidence, and embedding insights into commercial planning, medical strategy, evidence generation, and clinical operations execution.

• Continuously identify opportunities to modernize tools, platforms, processes, and AI-enabled workflows that improve the impact, efficiency, and scalability of analytics delivery.

Education Required:

• Bachelor’s degree required in a quantitative field such as biostatistics, statistics, mathematics, economics, data science, computer science, or a related discipline; Advanced degree preferred

Qualifications:

• Bachelor’s degree in a required field with 12 + years of overall experience and 10 + years of experience in advanced analytics, data science, commercial analytics, medical analytics, clinical operations analytics, business analytics, or a related function within the pharmaceutical, biotech, healthcare, or life sciences sector.

• Demonstrated experience translating complex data and analytics into strategic recommendations for senior business stakeholders.

• Strong understanding of healthcare, medical, clinical, and commercial data sources, such as claims, prescription, specialty pharmacy, EHR, real-world data, clinical trial operations data, market access, and third-party syndicated datasets.

• Experience leading analytics initiatives that support commercial strategy, omnichannel engagement, patient journey insights, medical engagement, evidence generation, clinical trial feasibility, enrollment, site performance, customer targeting, segmentation, measurement, or predictive modeling.

• Proven ability to lead cross-functional initiatives and influence stakeholders across business, technology, data, legal, compliance, and vendor teams.

• Demonstrated ability to identify high-value AI opportunities, guide stakeholders through AI-enabled transformation, and translate emerging technologies into practical business, scientific, and operational applications.

• Bachelor’s degree in statistics, data science, economics, engineering, business analytics, computer science, or a related quantitative field, or equivalent practical experience.

Preferred Qualifications:

• Advanced degree, such as a Master’s, MBA, or Ph.D., in a quantitative, scientific, technology, or business discipline.

• Experience with modern analytics, AI, and data platforms, such as cloud data warehouses, data science workbenches, business intelligence tools, SQL, Python, R, machine learning operations, generative AI tools, and AI/ML deployment approaches.

• Experience building or scaling analytics capabilities in a fast-paced, growth-oriented organization.

• Strong executive communication skills, including the ability to develop clear narratives, simplify complexity, and present insights to senior leadership.

• Familiarity with pharmaceutical data privacy, compliance, governance, responsible AI considerations, and the practical application of AI in regulated life sciences environments.

Supervisory Responsibilities:

• This position may manage internal analysts, external vendors, agency partners, or contractors and may provide project leadership or informal guidance to junior analysts; no direct people management is required unless otherwise determined by business need.

Travel:

• Up to 20% for team meetings, stakeholder workshops, or business reviews may be needed.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.