Director of Data Analytics and AI

Tasks and Responsibilities

• Develop and execute enterprise-wide data, digital, and AI strategy
• Establish and enforce data governance policies, standards, and frameworks
• Design and implement master data architecture, models, and hierarchies
• Ensure master data accuracy and consistency across customer, product, vendor, and operational domains
• Define and manage processes for creation and maintenance of master data
• Lead digital transformation initiatives including AI, analytics, and data platforms
• Identify opportunities for AI-driven optimization in operations and decision-making
• Develop reporting standards, dashboards, and advanced analytics capabilities
• Monitor emerging technologies and implement innovative digital solutions
• Establish AI governance including model lifecycle and risk management
• Lead, develop, and mentor global data and AI teams
• Collaborate with cross-functional stakeholders to align initiatives with business priorities
• Manage Data & AI budget and ensure cost efficiency and ROI
• Conduct data quality reviews, audits, and continuous improvement initiatives

Education and Experience

• Degree in Computer Science, Data Science, Information Management, or related field
• 10+ years of relevant experience in data, analytics, or digital leadership roles
• Proven experience in data governance and master data management
• Strong experience in enterprise data architecture and analytics platforms
• Experience leading digital transformation and AI initiatives
• Experience in global / multi-site environments
• Knowledge of data privacy regulations (e.g., GDPR, ITAR)
• Fluent English (spoken and written)

Competencies

• Strategic thinking and strong business acumen
• Leadership and team development capability
• Strong communication and stakeholder management skills
• Advanced analytical and problem-solving skills
• Ability to interpret complex data and drive insights
• Financial and budget management capability
• Strong execution and results orientation

Key Performance Indicators

• Data quality and master data accuracy
• Adoption of governance frameworks
• ROI of Data & AI initiatives
• Improvement in reporting efficiency and time-to-insight
• Adoption of analytics tools
• Stakeholder satisfaction

Travel required during key transformation phases, domestic and international (estimated <20%)