Senior Director, Data & AI Lead

The Senior Director, Tech Operations Data & AI Center of Excellence (CoE) is responsible for owning, governing, and scaling Data & AI capabilities across Tech Operations in alignment with Jazz’s enterprise hub-and-spoke operating model.

This role holder serves as the TechOps-facing hub leader, accountable for:

• TechOps Data & AI strategy and roadmap
• Demand shaping and value-based prioritization
• Adoption, capability uplift, and realized value
• End-to-end accountability for TechOps AI and advanced analytics outcomes, while leveraging DEC and enterprise DA+A hub capabilities for delivery capacity

The role holder partners closely with TechOps functional leaders, Digital Committees, AI Council, and enterprise CoEs to ensure Data & AI initiatives are business-led, governed, compliant, and scalable in a regulated pharmaceutical environment. This leader combines strategic vision, operating‑model leadership, and executive influence, ensuring Data & AI become practical, scalable, and responsible enablers of TechOps performance, reliability, and innovation.

Essential Functions/Responsibilities

TechOps Data & AI Strategy & Portfolio Ownership

• Owns and executes the TechOps Data & AI strategy and multi-year roadmap, aligned to enterprise Data & AI standards and TechOps digital priorities.
• Acts as the front door for TechOps Data & AI demand, shaping high‑value use cases, governing experimentation, and ensuring adoption and realized value across Manufacturing, Supply Chain, Quality, and Technical Operations.
• Drives value-based portfolio prioritization, sequencing initiatives through the established TechOps Digital Committee and investment governance forums.
• Retains end-to-end accountability for TechOps Data & AI outcomes, from ideation through scaled adoption.

Hub-and-Spoke Operating Model Leadership

• Leads the TechOps Data & AI CoE as the TechOps spoke, operating within Jazz’s broader hub-and-spoke Data & AI model.
• Clearly defines and enforces role clarity between:
• TechOps CoE ownership (use case shaping, adoption, value realization).
• Enterprise hubs (DEC / DA+A) for platform, architecture, data engineering, ‘MLOps’, and security capabilities.
• Ensures consistent application of enterprise standards, guardrails, and patterns, while tailoring solutions to TechOps needs.

Governance, Risk & Responsible AI

• Ensures all TechOps Data & AI initiatives comply with Jazz AI principles, regulatory requirements, security, privacy and validation standards.
• Partners with the AI Council to flag AI‑impacting initiatives and guide responsible experimentation.
• Champions ethical, explainable, and compliant AI practices across TechOps.

Experimentation, Scaling & Delivery Enablement

• Sponsors and governs experimentation, proofs-of-concept, and pilots, advancing only viable initiatives into scaled delivery.
• Works with DEC and enterprise DA+A teams to transition validated initiatives into production-ready solutions.
• Ensures solutions are operationalized into TechOps processes, systems, and decision-making workflows.

Adoption, Capability Building & L&D

• Owns the TechOps Data & AI capability uplift agenda, including learning pathways, role-aligned expectations, and champion networks.
• Drives adoption through change management, communications, and embedded data & AI fluency across TechOps.
• Tracks and reports on usage, adoption, and realized value, not just delivery milestones.

People & Partner Leadership

• Builds and leads a high-performing TechOps Data & AI CoE team, including employees, contingent workers and partners.
• Serves as a senior advisor to TechOps LT members, translating complex Data & AI topics into actionable business decisions.
• Influences without direct authority across enterprise hubs, functional spokes and governance bodies.

Qualifications & Experience

Required

• Proven record of leading enterprise‑scale Data, Analytics, or AI strategies with measurable outcomes.
• Strong understanding of advanced analytics, AI/ML concepts, and their application to industrial or operational environments.
• Demonstrated ability to operate effectively within federated or hub‑and‑spoke operating models.
• Experience partnering with platform, architecture, engineering, and governance teams.
• Exceptional leadership, communication, and executive‑level influencing skills.
• Strategic mindset with strong execution discipline.

Preferred

• Experience in pharmaceutical, biotech, or other highly regulated industries.
• Familiarity with MLOps, advanced analytics platforms and AI product operating models.
• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Engineering, Statistics, or related field preferred.
• Significant progressive experience in data, analytics, AI, or digital roles, including senior leadership responsibility.
• Track record of building data & AI literacy and adoption programs beyond technical teams.

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