OT Data & AI Product Owner

Own the OT Data & AI product vision and roadmap for shopfloor digitalization, ensuring alignment with OT Programs strategy, standards, and lifecycle governance, and delivering measurable operational value. 

Identify, size, and prioritize high‑value use cases across manufacturing and supply chain; translate needs into clear product outcomes and acceptance criteria in partnership with sites and key functions. 

Lead the idea‑to‑product pathway by shaping MVPs/PoCs, defining success metrics, and driving scale decisions (standardize / iterate / stop) through established governance based on value, feasibility, compliance, and cybersecurity readiness. 

Ensure product solutions align enterprise architecture and data standards (e.g., ISA‑88/95) by partnering with Enterprise architects and data governance teams—driving fit‑for‑purpose requirements and reusable foundations for global adoption. 

Own and prioritize the OT Data & AI product backlog (epics/features/user stories) based on value, risk, compliance, cybersecurity, and capacity; maintain transparency on priorities and trade‑offs. 

Define product vision, roadmap, and release plan (quarterly) with measurable outcomes and KPIs (adoption, cycle‑time improvements, right‑first‑time, scrap/rework reduction, etc.). 

Elicit and manage requirements across sites/functions (Manufacturing Quality,  Engineering, Data & Digital & Technology (DD&T)), translating needs into clear product outcomes, user stories, and testable acceptance criteria aligned to OT standards, data governance, and lifecycle controls. 

Drive MVP/PoC execution through cross‑functional teams and vendors: coordinate discovery‑to‑delivery activities; define hypotheses, success criteria, and acceptance tests; run demos, feedback loops, and iteration cycles. 

Own product value tracking: define KPIs, baseline current performance, and report realized/expected value; recommend continue/stop/scale decisions via governance. 

Ensure scale readiness and lifecycle handover: documentation, support model, training, operational readiness, validation/testing evidence (incl. data integrity and audit readiness considerations), prior to transition into deployment programs. 

Partner with DD&T architects and data governance to ensure alignment with the OT data lake blueprint, data‑flow patterns, contextualization (ISA‑88/95), and DD&T requirements—without duplicating architecture ownership. 

Manage product risks and controls: identify/mitigate compliance, data integrity, cybersecurity, and operational risks; ensure products meet regulated environment expectations and audit readiness. 

Represent OT Data & AI product topics in forums/communities of practice; drive reuse of successful patterns, lessons learned, and standard work across the network. 

Act as escalation point for product scope decisions (priority conflicts, value trade‑offs, and release readiness), coordinating resolution with Quality/Validation/Cybersecurity and platform owners per governance. 

Education & Experience: Bachelor’s (or higher) in Engineering, Computer Science, Data/Automation, or related field; typically 7+ years in OT/digital manufacturing and/or data/AI products in industrial environments, with proven experience in OT/digital manufacturing product ownership (backlog/roadmap/release/value tracking) and delivering scalable OT data/AI capabilities in regulated industries (e.g., pharma/life sciences preferred); working knowledge of GxP/CSV, data integrity, and OT cybersecurity; experience managing vendors/system integrators. 

Behavioural & Leadership Competencies: Strong analytical and strategic thinking; sound judgment; ability to influence across functions/cultures; effective communication in complex global environments; continuous improvement mindset while navigating ambiguity. 

Professional & Functional Skills: Proven expertise in Data & AI product delivery across the innovation lifecycle; strong understanding of OT cybersecurity and interoperability fundamentals; experience in global matrixed organization.