Overview In this role you will lead the ADS team within Zoetis VM RD to shape a modern, scalable data ecosystem that supports discovery, regulatory submission, and data-driven decisions. You will partner with scientists, clinicians, and regulators to implement governance, FAIR data practices, and AI/ML initiatives at scale. The position focuses on delivering high-quality, compliant data products and end-to-end platforms that accelerate R&D while reducing cycle times. You will drive impact through cross-functional leadership, strategic roadmapping, and measurable scientific outcomes. This is an opportunity to influence how data and digital solutions transform animal health research and development. ResponsibilitiesLead and grow teams across data engineering, analytics, data science, and product management to deliver high-quality solutionsOwn and prioritize the R&D digital strategy and portfolio to maximize value, speed, and complianceDefine and scale the R&D AI and data science strategy with measurable scientific impactDeliver $30M+ R&D data and digital programs through end-to-end, compliant solutionsGovern the R&D data and digital roadmap with regulatory/privacy obligations and audit readinessEnforce standard data architecture, metadata, and FAIR principles with quality controls and lineageBuild self-service data products and insight platforms with strong UX and agile deliveryCollaborate with IT to establish an operating model for enterprise-scale R&D platforms and cost optimizationDefine and track KPIs to measure outcomes and promote continuous improvementOrchestrate cross-domain data integration from discovery to product submission, improving reproducibility and throughputLaunch communities of practice and training, embedding responsible AI practices Key requirementsBachelor in Computer Science8+ years in information/digital/data technology roles delivering large-scale solutions4+ years in people management3+ years in health sciences industry desiredleadership and people managementcross-functional collaborationstakeholder engagementdata engineering and analytics leadershipdata governance and FAIR principlesAI/ML strategy and implementations
Not specified in the original listing.
Not specified in the original listing.
