Senior Director, Data Product Delivery
Fujifilm is globally headquartered in Tokyo with over 70,000 employees across four key business segments of healthcare, electronics, business innovation, and imaging. We are guided and united by our Group Purpose of "giving our world more smiles." Visit: Job Description What you'll do
- Be the executive face of digital, data, and AI for strategic customers: chair governance and steering forums, keep communication transparent, and lock outcomes to client objectives in partnership with global program managers.
- Orchestrate end-to-end delivery of customer data products: from scoping and contracting through discovery, build, validation, deployment, and sustainment-hitting agreed quality bars and value targets every time.
- Turn the portfolio into clear executive insight: deliver crisp reporting on status, risks, financials, and outcomes to senior leadership and customer stakeholders.
- Set the playbook for delivery excellence: champion the right methodology for the mission-Agile, Waterfall, or hybrid-tailored to data and AI initiatives with the strategy team.
- Optimize capacity to maximize impact: plan resources, prioritize demand, and balance a global data/analytics/AI portfolio to protect timelines and value.
- Build a powerhouse team: lead and coach senior contributors across sites, set vision and priorities, drive engagement, and deliver outcomes on-time and on-budget-while growing careers and fostering a high-performance, compliant culture.
- Make compliance a competitive advantage: partner with IT Compliance to embed GxP/CSV, GDPR/data privacy, AI ethics/guardrails, and corporate quality standards across every project activity.
- Keep programs on the rails: track milestones, interdependencies, and critical paths; run portfolio tooling and dashboards; synthesize insights for leadership and customer reporting.
- Ignite AI fluency and adoption: lead internal initiatives that raise AI literacy, strengthen governance, and scale responsible AI practices across the organization.
- And more as we grow: jump on high-impact opportunities that protect operations, elevate customer satisfaction, and unlock new value.
- Bachelor's degree in Computer Science, Engineering, Data Science, Business, or related field (required)
- Advanced degree strongly preferred (e.g., MBA, MSc)
- Certifications: PgMP or PMP (required)
- Additional certifications preferred: Agile/SAFe (e.g., POPM), Lean Six Sigma (Green/Black Belt); product management certification (e.g., Pragmatic/PMC) is a plus
- 12+ years of progressive product/program/portfolio delivery in technology, including 8+ years leading global product delivery or PMO functions
- Proven success delivering complex, multi-stakeholder data and AI/analytics products at enterprise scale, including customer-facing engagements and vendor/partner ecosystems
- 5+ years in data/analytics/AI domains with working knowledge of data architectures, data platforms, MLOps/ModelOps, and data governance
- 10+ years managing, leading, and developing people
- Hands-on experience operating in regulated, quality-driven environments (e.g., life sciences, healthcare) with strong compliance outcomes (GxP, GDPR/data privacy, AI ethics, ISO/ITGC)
- Track record driving digital transformation, including data and AI adoption and literacy
- Executive presence with experience briefing senior stakeholders, chairing steering committees, and leading cross-functional decision forums
- Proficiency with PPM and delivery tools (e.g., ServiceNow, Smartsheet, Azure DevOps), analytics/BI (e.g., Power BI/Tableau), and collaboration platforms; familiarity with Planner or similar
- Advanced degree (MBA, MSc)
- Agile/SAFe and Lean Six Sigma certifications; product management certification (Pragmatic/PMC or equivalent)
- Deep experience in highly regulated industries (life sciences/biopharma, healthcare) and audit-ready delivery (GxP/CSV, GDPR/data privacy, AI governance)
- Leading global, matrixed teams and vendor/partner ecosystems to deliver customer-facing data products
- Implementing MLOps/ModelOps and data governance at scale, including AI risk management and guardrails
- Portfolio financial management, business casing, cost-to-serve optimization, and SOW/vendor management
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