VP, Applied AI, Data Science & Commercial Intelligence

Ideal location: East Hanover, NJ. Remote work may be possible in certain states; remote associates cover home-office costs and may incur periodic travel/lodging expenses. On-site associates may receive relocation assistance to within 50 miles of the site. This role requires 10% travel (domestic and/or international).

About The Role

The VP, Applied AI, Data Science & Commercial Intelligence will lead the strategy, development, and adoption of applied AI, data science, and commercial intelligence capabilities to accelerate business growth and decision-making. This executive role partners across commercial, technology, and business functions to translate data and AI into measurable business outcomes while building scalable platforms, high-performing teams, and a culture of innovation.

Responsibilities

• Define and execute the enterprise strategy for applied AI, data science, and commercial intelligence aligned with business priorities.
• Lead multidisciplinary teams spanning AI, machine learning, data science, analytics, and commercial insights.
• Develop and deploy AI-powered products and decision-support solutions that improve customer engagement, commercial performance, and operational efficiency.
• Partner with business leaders to identify, prioritize, and deliver high-value AI and analytics use cases with measurable ROI.
• Establish best practices for AI governance, model lifecycle management, responsible AI, and data quality.
• Build scalable AI and data platforms that enable reusable models, standardized capabilities, and rapid innovation.
• Recruit, mentor, and develop world-class technical and product talent while fostering a culture of collaboration and continuous learning.

Requirements

• Advanced degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative discipline.
• 15+ years of progressive leadership experience across applied AI, data science, analytics, commercial intelligence, digital product, or technology transformation, including enterprise-level strategy and senior team leadership.
• Experience in pharmaceutical, healthcare, life sciences, biotech, or another regulated data-rich industry, ideally with commercial and enterprise transformation exposure.
• Proven record setting AI/data strategy and scaling AI-enabled products, decision intelligence, commercial analytics, and enterprise platforms that drive measurable growth, productivity, adoption, and business outcomes.
• Strong executive fluency across machine learning, GenAI, agentic AI, LLMs, RAG, data engineering, MLOps/LLMOps, cloud platforms, experimentation, model lifecycle management, AI governance, and data quality.
• Deep understanding of commercial business value drivers, including customer engagement, field effectiveness, omnichannel, launch excellence, content/personalization, market access, insights, forecasting, and operational efficiency.
• Demonstrated ability to translate business strategy into portfolio priorities, investment decisions, capability roadmaps, operating models, adoption plans, and value realization metrics.
• Enterprise leadership capability to align Commercial, SPT, DDIT, Product, Engineering, Legal/Privacy, Compliance, Security, Finance, and senior business leaders around responsible AI adoption and measurable impact.

Preferred Experience and Skills

• Experience leading adoption of generative AI, agentic AI, commercial intelligence, AI product innovation, or large-scale analytics transformation across countries, business units, or functions.
• Advanced degree preferred in Computer Science, Data Science, Statistics, Engineering, AI/ML, Operations Research, Economics, Bioinformatics, or a related quantitative/business discipline.
• External thought leadership, partner/vendor ecosystem experience, and demonstrated ability to attract, develop, and retain senior AI, data science, product, and platform talent.

Performance Metrics

• Delivery of agreed product, platform, program, strategy, AI, or knowledge-engineering milestones within planned timelines.
• Stakeholder satisfaction, user adoption, business outcomes, and measurable value realization for assigned capabilities.
• Quality and completeness of strategy, roadmap, governance, delivery, technical, and executive reporting artifacts.
• Alignment with enterprise architecture, Responsible AI, data governance, security, accessibility, and applicable regulatory requirements.
• Team effectiveness, operating model maturity, risk transparency, and continuous improvement against agreed success metrics.

Pay

Salary range: $303,100.00 – $562,900.00 annually. Final salary determined based on relevant skills and experience. Compensation includes a performance-based cash incentive and eligibility for annual equity awards.

Benefits

• Comprehensive health, life, and disability benefits.
• 401(k) with company contribution and match.
• Generous time off package including vacation, personal days, holidays, and other leaves.