Executive Director, Global Commercial Analytics- Decision Science

Vertex Pharmaceuticals•Boston, MA

About The Position

The Executive Director, Global Commercial Analytics- Decision Science will lead the global Decision Science capability within Global Commercial Strategy. Reporting to the Vice President, Global Commercial Analytics, this leader will build an integrated team that frames priority business decisions, translates them into analytical questions, and applies advanced analytics to inform pipeline development and improve commercial, launch, and portfolio choices. The Executive Director will establish common standards, methodologies, and scalable capabilities across segmentation, targeting, patient finding, resource allocation, scenario modeling, experimentation, and measurement. Working through disease-aligned Decision Science leads, the role will ensure analytics are embedded in decision-making and translated into clear recommendations and measurable business impact. At Vertex, employees are encouraged to keep informed about advances in AI, technology, automation, and industry trends. The company seeks people who bring an external perspective, demonstrate curiosity and sound judgment, and thoughtfully adopt capabilities that improve decision-making, drive innovation, increase efficiency, and help deliver better outcomes for patients.

Requirements

Minimum of a Bachelor’s degree in statistics, mathematics, economics, operations research, data science, engineering, business, or a related quantitative discipline.
Extensive leadership experience in commercial analytics, decision science, marketing science, advanced analytics, data science, or a related field within biopharmaceuticals or another complex, data-rich industry.
Demonstrated experience translating ambiguous business questions into analytical frameworks and actionable recommendations for senior commercial leaders.
Deep expertise across several Decision Science disciplines, such as segmentation and targeting, patient analytics, resource allocation, marketing mix and promotional effectiveness, experimentation, causal inference, predictive modeling, and optimization.
Experience applying pharmaceutical and healthcare data, including patient-level, claims, prescription, customer, promotional, and other secondary data, to commercial decisions.
Experience supporting global portfolios across pipeline, launch, lifecycle, and in-line stages and operating across global, regional, and local organizations.
Demonstrated ability to build scalable analytical capabilities, common methodologies, governance, and reusable data or decision-support products.
Strong understanding of AI and machine learning and sound judgment on how to validate, govern, operationalize, and measure AI-enabled decision support.
Proven success leading and developing multidisciplinary analytical teams and influencing through a highly matrixed organization.
Exceptional strategic thinking, analytical rigor, business judgment, executive communication, and ability to simplify complex analyses without losing critical nuance.
Experience managing external partners, analytical investments, and multiple priorities while maintaining high standards for quality, privacy, compliance, and business impact.

Nice To Haves

Advanced degree such as an M.S., Ph.D., or MBA.

Responsibilities

Lead the Global Decision Science organization and capability agenda across pipeline, pre-launch, launch, lifecycle, and in-line disease areas.
Partner with GCS disease leaders and BI&A pod leads to frame priority business decisions, define analytical questions, and identify evidence required to act.
Establish standards and methodologies for segmentation, targeting, patient finding, customer and patient analytics, resource allocation, scenario modeling, and commercial optimization.
Build advanced analytical approaches to quantify key drivers, risks, trade-offs, and likely business impact across commercial and portfolio decisions.
Lead experimentation and measurement capabilities, including test-and-learn design, causal measurement, promotional effectiveness, and assessment of whether recommendations improve outcomes.
Develop scalable decision-support solutions combining analytical models, business rules, internal and external data, and AI-enabled capabilities.
Ensure models and recommendations are transparent, fit for purpose, appropriately validated, and grounded in strong business and market understanding.
Build reusable data assets and analytical products for commercialization, including patient-level analyses, claims-based insights, HCP universes, and opportunity-prioritization tools.
Partner with Market Research, Forecasting, Competitive Intelligence, Portfolio Analytics, and Data Management & Capabilities to create integrated evidence and avoid fragmented analyses.
Work with regional Commercial, Medical, Value & Access, HEOR, Finance, and Digital/Data/Technology teams to align analytical approaches, data requirements, and adoption.
Translate complex analyses into clear implications, decision options, recommendations, and executive-ready narratives; constructively challenge assumptions when evidence indicates a different course.
Establish governance, prioritization, quality standards, vendor strategy, and a capability roadmap for Decision Science.
Build, develop, and retain a high-performing global team; create clear roles, career paths, technical standards, and a culture of analytical rigor, curiosity, collaboration, and accountability.
Measure the adoption, quality, efficiency, and business impact of Decision Science capabilities and continuously improve the operating model.

Benefits

Annual bonus eligibility
Annual equity awards
Medical benefits
Dental benefits
Vision benefits
Generous paid time off, including a week-long company shutdown in the Summer and the Winter
Educational assistance programs, including student loan repayment
Commuting subsidy
Matching charitable donations
401(k)