Process Analysis & Adoption Lead in Kalamazoo, Michigan

Senior Principal Scientist - Process Analysis & Adoption (PAA) Lead - VMRD Automation & Data Sciences

In close partnership with scientific, clinical, and regulatory stakeholders, this role will lead a team that evaluates, optimizes, and drives adoption of cross-functional R&D processes to accelerate discovery through development and serve as the connection between scientists, ADS technical teams, Zoetis Tech & Digital (ZTD), and external services. The role owns the end-to-end process improvement and change adoption portfolio, from discovery and analysis through solution definition, delivery readiness, training, and benefits realization, ensuring solutions are business-led, user-centered, and measurably improve cycle time, quality, compliance, and reuse of scientific data.

The ideal candidate blends process excellence and change leadership with business analysis rigor, translating lab and study needs into actionable requirements and adoption plans s role emphasizes leadership in collaboration, change management, and cross-functional innovation to enhance Zoetis' ability to deliver innovative therapeutics, vaccines, biodevices, and diagnostics.

• Evolve and lead the PAA team (process analysts, change/adoption specialists, and business analysts), fostering a culture of curiosity, delivery excellence, and continuous improvement.
• Define team operating norms, roles, responsibilities, and quality standards; manage PAA capacity, assignments, and workload across initiatives.
• Own the VMRD process analysis and adoption portfolio: prioritize opportunities with scientific leaders; define scope, success metrics, and sequencing; manage benefits tracking and reporting.
• Lead structured process discovery and optimization with an Agile methodology focus:
• Define epics and user stories, mapping current/future states, quantifying constraints, and designing right-sized interventions.
• Ensure relevant source materials (e.g., SOPs, templates, worksheets, reports, system references) are gathered before workshops and discovery sessions; distinguish what can be learned from documentation vs. direct stakeholder engagement.
• Establish a practical adoption planning approach aligned with product discovery, delivery, release, and post-launch support; ensure post-launch feedback is captured and used to improve adoption and future iterations.
• Identify impacted stakeholder groups, readiness concerns, adoption barriers, training needs, and communication needs early enough to influence product and delivery decisions.
• Drive cross-use-case pattern recognition so process learnings and adoption insights are reusable across products and future work streams.
• Drive business analysis for digital and lab automation initiatives:
• Elicit, synthesize, and validate user stories and acceptance criteria. Ensure that acceptance criteria align with FAIR principles, where pertinent. Partner with internal ADS product owners, data/automation engineers, ZTD, and external implementation partners (technical consultants and product leads) to shape feasible, scalable solutions and ensure clear delineation of responsibilities between internal teams and vendor resources. Partner with business leads to define Key Performance Indicators to quantify, where practical, the benefits of digital investments.
• Orchestrate adoption and change management:
• Create stakeholder analyses, communications, training curricula, and hypercare plans.
• Establish and run communities of practice and role-based enablement.
• Monitor adoption KPIs (e.g., activation, engagement, task success) and remove barriers to usage.
• Establish and maintain standard PAA templates, methods, and deliverables (e.g., stakeholder maps, data source capture templates, process documentation, adoption plans, readiness assessments, risk logs, feedback summaries); ensure consistent use and storage in the agreed source of truth.
• Define and implement success metrics and measurement plans for each initiative (e.g., cycle time deltas, documentation touch time, error/redo rates, compliance conformance, data completeness/lineage).
• In coordination with Quality and Compliance, ensure processes and supporting digital solutions meet relevant regulatory and quality expectations (e.g., GxP contexts, data integrity) where applicable.
• Partner with program management to align dependencies, risks, and milestones; ensure readiness for deployment (process, people, and data) and smooth handoffs to operations.
• Maintain a living library of instructional materials supporting digital initiatives in the appropriate location to ensure access, continuity and audit compliance. Scan industry trends and benchmark best practices in lab digitalization, data capture/visualization, and scientific workflow optimization; pilot and scale high-ROI innovations.
• Coach and mentor PAA specialists and cross-functional colleagues; elevate organizational capabilities in process thinking, requirements discipline, and adoption planning.

Requirements

• Education:
  
  Bachelor's degree in a relevant field…