VP, Applied AI, Data Science & Commercial Intelligence

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. 

Responisbilites:

• 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. 

Required experience: 

• 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 skill set: 

• 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. 

• 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. 

The salary for this position is expected to range between $303,100.00 and $562,900.00 annual per year. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.