Process Analysis & Adoption Lead
Zoetis
August 18, 2026
Remote friendly (Kalamazoo, MI)
United States
Operations
Position Summary
- Partner with scientific, clinical, and regulatory stakeholders to lead evaluation, optimization, and adoption of cross-functional R&D processes to accelerate discovery through development.
- Own the end-to-end process improvement and change adoption portfolio (discovery/analysis → solution definition → delivery readiness → training → benefits realization), improving cycle time, quality, compliance, and reuse of scientific data.
- Drive cross-functional innovation through leadership, change management, and collaboration.
Essential Duties and Responsibilities
- Evolve and lead the PAA team; define operating norms, roles, responsibilities, quality standards, and manage capacity/workload.
- Own the VMRD process analysis and adoption portfolio (prioritize opportunities, define scope/success metrics/sequence, manage benefits tracking/reporting).
- Lead Agile-focused structured process discovery/optimization (define epics/user stories; map current/future states; gather source materials; align adoption planning with discovery/delivery/release/post-launch; identify stakeholders, readiness concerns, barriers, training, and comms).
- Enable reuse via cross-use-case pattern recognition.
- Conduct business analysis for digital/lab automation (validate user stories/acceptance criteria aligned to FAIR where pertinent; partner with ADS/ZTD and vendors; define KPIs for digital benefits).
- Orchestrate adoption/change management (stakeholder analyses, communications, training curricula, hypercare; communities of practice; monitor adoption KPIs and remove barriers).
- Establish standard PAA templates/methods; define initiative success metrics/measurement plans; coordinate with Quality/Compliance for GxP/data integrity where applicable; align program dependencies/risks/milestones and ensure readiness/handoffs.
- Maintain instructional materials library, benchmark/pilot high-ROI innovations, coach/mentor specialists.
Requirements
- Education: Bachelor’s in relevant field (life sciences, engineering, operations research, info systems, or related); advanced degree preferred.
- Experience: 10+ years process analysis/improvement and adoption in life sciences/regulated R&D; 3+ years people leadership; 5+ years Agile in R&D product/platform context (epics/user stories, acceptance criteria, backlog hygiene); delivered multi-team transformations with measurable outcomes; strong business analysis (requirements elicitation, process/data modeling, refinement).
- Skills: Agile/Scrum (acceptance criteria, backlog refinement), familiarity with Waterfall/SDLC; BRDs/FRDs, BPMN/UML/use cases; process mapping; stakeholder facilitation; UAT planning/execution and defect triage support.
- Change management toolkit (e.g., PROSCI/ADKAR) and learning design; tool proficiency (e.g., Miro, discovery/process templates, stakeholder/journey maps, adoption plans, shared repositories).
- Knowledge of scientific workflows/tools (material registration, ELN/LIMS, instrument data capture, lab automation) and FAIR; Lean/Six Sigma certification preferred.
- Familiarity with data products/analytics, metadata, data quality/lineage, source-of-truth concepts.
- Organized, resilient, delivery-focused; navigate ambiguity and matrixed teams.
- Partner with scientific, clinical, and regulatory stakeholders to lead evaluation, optimization, and adoption of cross-functional R&D processes to accelerate discovery through development.
- Own the end-to-end process improvement and change adoption portfolio (discovery/analysis → solution definition → delivery readiness → training → benefits realization), improving cycle time, quality, compliance, and reuse of scientific data.
- Drive cross-functional innovation through leadership, change management, and collaboration.
Essential Duties and Responsibilities
- Evolve and lead the PAA team; define operating norms, roles, responsibilities, quality standards, and manage capacity/workload.
- Own the VMRD process analysis and adoption portfolio (prioritize opportunities, define scope/success metrics/sequence, manage benefits tracking/reporting).
- Lead Agile-focused structured process discovery/optimization (define epics/user stories; map current/future states; gather source materials; align adoption planning with discovery/delivery/release/post-launch; identify stakeholders, readiness concerns, barriers, training, and comms).
- Enable reuse via cross-use-case pattern recognition.
- Conduct business analysis for digital/lab automation (validate user stories/acceptance criteria aligned to FAIR where pertinent; partner with ADS/ZTD and vendors; define KPIs for digital benefits).
- Orchestrate adoption/change management (stakeholder analyses, communications, training curricula, hypercare; communities of practice; monitor adoption KPIs and remove barriers).
- Establish standard PAA templates/methods; define initiative success metrics/measurement plans; coordinate with Quality/Compliance for GxP/data integrity where applicable; align program dependencies/risks/milestones and ensure readiness/handoffs.
- Maintain instructional materials library, benchmark/pilot high-ROI innovations, coach/mentor specialists.
Requirements
- Education: Bachelor’s in relevant field (life sciences, engineering, operations research, info systems, or related); advanced degree preferred.
- Experience: 10+ years process analysis/improvement and adoption in life sciences/regulated R&D; 3+ years people leadership; 5+ years Agile in R&D product/platform context (epics/user stories, acceptance criteria, backlog hygiene); delivered multi-team transformations with measurable outcomes; strong business analysis (requirements elicitation, process/data modeling, refinement).
- Skills: Agile/Scrum (acceptance criteria, backlog refinement), familiarity with Waterfall/SDLC; BRDs/FRDs, BPMN/UML/use cases; process mapping; stakeholder facilitation; UAT planning/execution and defect triage support.
- Change management toolkit (e.g., PROSCI/ADKAR) and learning design; tool proficiency (e.g., Miro, discovery/process templates, stakeholder/journey maps, adoption plans, shared repositories).
- Knowledge of scientific workflows/tools (material registration, ELN/LIMS, instrument data capture, lab automation) and FAIR; Lean/Six Sigma certification preferred.
- Familiarity with data products/analytics, metadata, data quality/lineage, source-of-truth concepts.
- Organized, resilient, delivery-focused; navigate ambiguity and matrixed teams.