Director, Advanced Analytics and Data Science - Innovation

Key Responsibilities

Analytics Strategy and Capability Development

• Contribute to and help execute the advanced analytics capability and innovation roadmap, aligning analytics investments with priorities across Commercial, Medical Affairs, and Clinical Operations and measurable enterprise outcomes.
• Advance practical AI innovation like predictive triggers, dynamic targeting, enhanced patient journey, next best action – HCP and Accounts, integrated account strategy etc. by identifying, piloting, and scaling use cases for generative AI, agentic AI, natural language interfaces, intelligent automation, and decision intelligence across Commercial, Medical Affairs, and Clinical Operations.
• 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.
• Build measurement frameworks for analytics and AI solutions, including success metrics, test-and-learn design, adoption tracking, performance monitoring, and outcome measurement to quantify business, scientific, operational, and patient impact.

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, measurable success criteria, 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, appropriate governance, and ongoing performance measurement 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 and hands-on driver in the responsible adoption and continuous evolution of advanced analytics, AI innovation, and machine learning capabilities across Commercial, Medical Affairs, and Clinical Operations teams.
• Provide day-to-day leadership, coaching, and guidance to data scientists, analysts, analytics partners, and external resources, while supporting team development and capability building.
• Establish practical operating models, standards, and best practices that improve analytics quality, scalability, speed to insight, measurement consistency, and reuse across teams.
• 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, scalability, adoption, and measurable value of analytics delivery.

Qualifications

Required Qualifications

• BA/BS Degree with 10+ years of overall industry experience with 8+ 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 and innovations that support commercial strategy, omnichannel engagement, patient journey insights, medical engagement, evidence generation, clinical trial feasibility, enrollment, site performance, customer targeting, segmentation, measurement, experimentation, 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 innovation opportunities, support AI-enabled transformation, and translate emerging technologies into practical business, scientific, and operational applications with clear measurement plans.
• Experience designing measurement approaches for analytics and AI initiatives, including KPI definition, experimentation, model monitoring, adoption metrics, and business impact assessment.
• 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, experimentation platforms, and AI/ML deployment and monitoring approaches.
• Experience building or scaling analytics capabilities, AI innovation pilots, measurement programs, or test-and-learn frameworks 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, coaching, or matrixed guidance to junior analysts; direct people management may be required based on business need.

Travel

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