Associate Vice President - Applied Intelligence for Discovery (AI4D)

Key Responsibilities

• Build and lead a multidisciplinary team spanning data science, ML engineering, and scientific software development
• Set technical vision and roadmap for AI/ML platforms serving discovery research, aligning capabilities with enterprise priorities
• Own the full platform lifecycle — from identifying and integrating new AI capabilities to sunsetting legacy solutions, optimizing for overall portfolio performance as research priorities evolve
• Guide architecture decisions for end-to-end ML workflows: data pipelines, feature engineering, model development, deployment, and monitoring
• Serve as executive champion for AI capabilities, articulating value to senior stakeholders and influencing resource allocation
• Identify, establish, and manage strategic partnerships with technology providers and research institutions to expand platform capabilities
• Drive adoption of MLOps practices that enable reproducible, automated, and compliant AI development at scale
• Partner with technology and therapeutic area leaders to envision and execute on high-impact AI applications and translate research requirements into platform capabilities
• Work across organizational boundaries in a complex matrixed environment to align platform strategy with scientific priorities

Qualifications

• Advanced degree (MS/PhD) in Computer Science, Data Science, Computational Biology, or related field
• 10+ years experience in AI/ML or data science, with 5+ years leading teams

Additional Skills/Preferences

• Proven track record driving AI/ML from concept to scaled deployment in complex matrixed organizations
• Deep expertise in modern ML frameworks, MLOps practices, and cloud platforms (AWS/Azure/GCP)
• Demonstrated track record of driving AI/ML capabilities from concept through scaled deployment in complex, matrixed organizations — with evidence of measurable impact on business outcomes, not just model performance
• Ability to translate between scientific research questions and technical solutions
• Experience navigating cross-functional dynamics and influencing without direct authority
• Experience in pharmaceutical, life sciences, or healthcare industries
• Track record managing external technology partnerships and vendor relationships
• Platform architecture background — you think in systems and portfolios, not features and projects