Key Responsibilities

Global Commercial Data & AI Strategy

• Own the enterprise commercial data, analytics, AI, and decision intelligence strategy.

• Define the long-term roadmap for how commercial data, advanced analytics, AI, and governance capabilities evolve to support business growth.

• Establish enterprise priorities and investment strategies for commercial intelligence capabilities.

• Ensure alignment between commercial business strategy, data strategy, AI strategy, and commercial technology roadmaps.

• Partner with Commercial Data Products and Commercial Data Analytics Engineering to define decision science use cases, business requirements, and operationalize analytics models.

AI & Advanced Analytics Leadership

• Lead the development and deployment of advanced analytical solutions across sales, forecasting, market development, customer success, and commercial operations.

• Build and scale machine learning, predictive analytics, optimization, simulation, experimentation, and recommendation engines.

• Drive adoption of modern AI capabilities including generative AI, agentic AI, copilots, reasoning systems, knowledge discovery, and intelligent workflow automation.

• Maintaindeepunderstanding of advancements in AI, economic conditions, market trends, and competitive forces shaping the future of commercial execution.

• Assess emerging technologies including agentic AI, reasoning systems, simulation platforms, digital commercial assistants, and real-time decision intelligence capabilities.

Data Governance & Trust

• Establish governance-by-design principles that embed trust, quality, compliance, and stewardship into workflows rather than relying on manual processes.

• Define enterprise standards for metadata management, lineage, cataloging, master data, data quality, retention, access management, and business semantics.

• Establish and govern enterprise KPI definitions, metric hierarchies, commercial data standards, and semantic consistency across Business Units and Regions.

• Lead governance councils and stewardship forums supporting commercial data and AI.

• Serve as the ultimate point of accountability for commercial data trust, adoption, transparency, quality, and usability.

Commercial Insights & Strategic Growth

• Establish enterprise frameworks for predictive, prescriptive, and scenario-based decision making.

• Develop analytical assets thatidentifygrowth opportunities, revenue risks, whitespace opportunities, customer trends, territory optimization opportunities, and sales execution gaps.

• Drive executive-level business reviews using forward-looking insights and recommendations.

• Ensure analytical outputs are translated into actionable business decisions.

• Serve as a strategic advisor to executive leadershipregardingcommercial performance, market dynamics, growth opportunities, and resource allocation.

• Establish value realization frameworks that measure adoption, business impact, and return on investment from commercial analytics, AI, and decision intelligence initiatives.

• Lead the evolution from descriptive reporting to predictive and prescriptive decision intelligence capabilities that improve forecasting, resource allocation, customer engagement, and commercial productivity.

Responsible AI&Compliance Controls

• Own the commercial AI governance framework, including model risk management, AI policies, controls, and standards.

• Establish responsible AI principles covering explainability, bias mitigation, transparency, human oversight, and model monitoring.

• Partner with Legal, Privacy, Compliance, Cybersecurity, and IT to ensure AI and data usage meets evolving regulatory requirements.

• Define governance approaches for GenAI, LLMs, agentic systems, autonomous workflows, and future AI technologies.

• Adviseexecutive leadership on AI readiness, risk exposure, maturity, and investment decisions.

Talent & Organizational Leadership

• Build and lead a world-class team of data scientists, AI specialists, governance leaders, and advanced analytics professionals.

• Foster a culture of agility, learning, innovation, accountability, and business impact.

• Build and scale a multi-disciplinary organization spanning decision science, AI strategy, governance, business intelligence, and commercial analytics excellence.

• Develop organizational capabilities that keep pace with rapid advances in AI, analytics, governance, and commercial strategy.

• Serve as a mentor, strategist, and thought leader across the global commercial organization.

Qualifications

• 12+ years of progressive experience in decision science, data science, artificial intelligence, advanced analytics, commercial data strategy, data governance, or related fields.

• 7+ years of leadership experience leading data science, AI, analytics, governance, data strategy, or decision intelligence teams.

• Proven success applying predictive modeling, machine learning, optimization, experimentation, forecasting, causal analytics, and advanced analytics in commercial environments.

• Deep understanding of commercial data governance, metadata management, lineage, data quality, access controls, privacy, compliance, and enterprise risk management.

• Strong understanding of modern AI technologies including GenAI, LLMs, agentic systems, retrieval-augmented generation, and intelligent automation.

• Experience translating complex analytical, governance, and AI concepts into executive-level recommendations and business actions.

• Strong business acumen and understanding of commercial operations, revenue growth, sales effectiveness, customer engagement, and strategic planning.

• Experienceoperatingwithin global, matrixed organizations across multiple Business Units, Regions, and regulatory environments.

Education:Advanced degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, Business Analytics, Information Systems, or relatedfieldrequired.

Desired Skills & Experience

• Experience within MedTech, Life Sciences, Healthcare, or similarly regulated industries preferred.

• Expertisein applied machine learning, statistical modeling, optimization, experimentation, decision science, and causal analytics.

• Experience implementing governance-by-design approaches that embed controls into platforms, workflows, and product development processes.

• Experience building enterprise AI products and deploying models into production environments.

• Understanding ofmodern cloud analytics ecosystems, data product operating models, semantic layers, MDM, metadata management, and data quality tooling.

• Experienceestablishinggovernance councils, stewardship forums, decision rights, and executive reporting mechanisms for enterprise data and AI capabilities.

• Ability to influence senior leaders through evidence-based recommendations, practical governance models, and clear value-realization frameworks.

Leadership Attributes

• Strategic Futurist:Anticipateshow AI, market dynamics, competitive shifts, regulation, and technology innovation will reshape commercial execution.

• Decision Intelligence Leader:Focuses on improving the quality and speed of decisions, not just generating insights.

• Enterprise Collaborator:Builds strong partnerships across business, technology, risk, and operational functions.

• Outcome Driven:Relentlessly focused on adoption, value realization, revenue impact, and business results.

• Executive Influencer:Communicates complex concepts with clarity and confidence while shaping strategic direction.