Director, Enterprise Data & AI Strategy

Job Summary

The Director, Enterprise Data & AI Strategy is a strategic, visionary enterprise leader responsible for defining and executing an AI strategy with global data that accelerates digital transformation, enables insightful decision-making, and drives operations excellence. This role will oversee the framework and integration of AI capabilities, enterprise data and automation to deliver that business impact shaping the organization's long term data vision and governance model. The Director will report directly with the VP of IT, partner closely with executive leadership (in particular the Finance, to ensure data and AI investments align with strategic business goals, innovation and priorities.

Responsibilities

• AI & Automation Strategy: Focus on shaping the vision and transformation of AI and Data Management. Owns the enterprise AI & automation strategy by identifying innovation opportunities, scaling AI use cases, and embedding automation across business processes - develops and executes a roadmap for AI and intelligent automation initiatives focused on driving operational efficiency and ROI. Evaluates and implements emerging technologies, including generative AI, RPA, and machine learning models such as Power Automate, UI Path, Automation Anywhere, Fabric, or others. Collaborate with executive sponsors to prioritize AI investments.
• Team Leadership and Development: Build and lead a high-performing team of data scientists, database administrators, AI/ML and automation engineers. Foster a culture of innovation, collaboration, and continuous improvement.
• Project Governance: Oversees and manages the intake of project and enhancement requests, provides initial time, resource and cost estimates, and aligns priorities with leadership and key stakeholders. Oversees the delivery of MDM, AI, and Automation projects and enhancements, ensuring they align with the company’s strategic goals and are delivered on time and within budget. Monitors project progress and takes corrective actions as needed to mitigate risks while ensuring successful outcomes.
• Data Strategy & Governance: Oversees the enterprise data strategy & governance by establishing enterprise standards for data ethics and AI governance. Defines and implements enterprise-wide data governance policies, standards, and best practices. Ensure data quality, integrity, security, and compliance across all systems following CSV process requirements. Partners with executive leadership to ensure compliance with evolving regulations and frameworks. (GxP, GDPR, AI ACT)
• Business Analysis: Develops a deep understanding of data flows supporting core business processes; Order to Cash, Procure to Pay, Demand to Build, Record to Report, Hire to Retire, Regulatory and Compliance. Reviews and approves requirements written by the business analysis team. Collaborates with business analysts to ensure clear and comprehensive documentation of project needs.
• Analytics & Business Intelligence: Shapes enterprise BI and analytics roadmap, enabling predictive insights and AI driven decision making for the C-suite and business units.
• Governance, Risk, and Compliance: Possesses a deep understanding of IT General Controls, GxP regulations and CSV standards. Ensures that all projects adhere to SOX, GxP compliance/Data Integrity requirements and partner with Quality to maintain compliance. Collaborates with cross-functional teams to address and resolve Quality or Audit Findings.
• Stakeholder Management: Builds and maintains strong relationships with key business stakeholders, ensuring clear communication and alignment of data initiatives with business needs and budgets. Communicates complex technical concepts to non-technical stakeholders effectively.
• Budget & Resource Allocation: Partnering closely with the VP of IT, this person will owns the data and AI portfolio budget, to optimize spend across global programs. Manages resource allocation effectively, balancing project needs with team capabilities and workload.
• Process Improvement: Continuously evaluates and improves core Procure to Pay, Demand to Build, Order to Cash, and Financial processes, incorporating best practices and innovative solutions.
• Vendor Management: Develops strategic partnerships with global technology vendors, consulting partners, and AI innovators to advance enterprise capabilities. Oversee relationships with key vendors, ensuring the effective delivery of services, visibility into application development roadmaps, advocating for business user enhancements, and alignment with business goals.