Senior Director, Business Insights & Analytics – Therapeutic Dermatology

Key Responsibilities

• Lead short/mid-range forecasting and performance tracking processes, by modeling numerous underlying demand and sales drivers, strategically working with stakeholders to define assumptions/parameters, communicating performance vs. forecast, and identifying critical scenarios/sensitivities and quantifying risks and opportunities.
• Lead definition of the strategic roadmap for business analytics and data modeling across the U.S. commercial business, aligning capabilities with commercial objectives and long-term growth plans.
• Own the full analytics lifecycle: data sourcing, processing, cleaning, modeling, visualization, and reporting, ensuring quality, consistency, and scalability.
• Own prioritization and governance of the analytics portfolio, balancing strategic initiatives with operational needs and ensuring on-time, high-impact delivery.
• Lead the design of advanced analytics frameworks and methodologies to detect trends, patterns, and drivers that address complex and evolving business challenges.
• Deliver enterprise-level insights that inform brand strategy, customer behavior, segmentation, forecasting, targeting, and ROI analysis, with clear implications for senior leadership decision making.
• Champion continuous improvement, identifying opportunities to enhance efficiency, automation, data quality, and self-service analytics capabilities across the organization.
• Translate analytical outcomes into clear, compelling narratives and recommendations for senior stakeholders, including executive leadership, and influence strategic choices.
• Serve as the senior subject matter expert and internal consultant on analytics, guiding business partners on how to best leverage data for commercial performance.
• Build, deepen, and sustain cross-functional strategic partnerships with marketing, sales, finance, IT, and other key functions to ensure analytics are integrated into core business processes and planning cycles.
• Own and optimize relationships with external vendors, data partners, and technology providers to support the analytics ecosystem and maximize value from external data assets.
• Mentor and develop analytics talent, fostering a high-performing, impact-oriented team culture and succession pipeline.

Qualifications

Education: Bachelor’s degree in quantitative discipline required (economics, business, finance, statistics, data science, engineering). Master’s degree or PhD strongly preferred.

Experience: 10+ years of progressive experience in analytics, insights, or data science within the pharmaceutical, biotech, or healthcare industry, and 5+ years of leadership experience in forecasting, marketing science or similar, and/or equivalent in relevant life sciences consulting role post-MBA/PhD, with meaningful quantitative decision support, and experience influencing senior leadership. Experience working with a range of data sets – specialty pharmacy/patient-level deidentified data, IQVIA data, payer/claims data, large unstructured data sets (e.g., social and digital media data, secondary data sources), etc., and strong proficiency in data visualization (e.g., Power BI, Tableau), analytics tools (e.g., Python, R, SQL), and CRM/data platforms. Demonstrated leadership of high-impact analytics teams, with a track record of building capabilities and leading complex, cross-functional initiatives at scale. Team player and collaborator with ability to develop rapport and credibility with a wide variety of stakeholders across different functions and at all levels. Exceptional problem-solving skills, strategic thinking, and the ability to translate complex technical findings into clear, actionable recommendations for non-technical executive audiences. Strong analytical skills and business acumen; intellectual curiosity, motivation and ability to structure problems, diagnose issues and triangulate with multiple approaches while keeping sight of the “big picture” and synthesize the key findings. Proven ability to drive change, establish analytics best practices, and embed data-driven decision making across a commercial organization.