VP of Data Analytics and AI
Core
Define and execute enterprise data, analytics, and AI strategy, roadmap, and investment plans to deliver scalable capabilities aligned with business strategy.
Role type
VP of Data Analytics and AI (Strategy & Leadership)
Builds
Enterprise data governance, data platforms, AI/ML solutions, and self-service analytics capabilities.
Domain
Enterprise Data & AI
Deliverable
production ML models
Required skills
Data governance, data management, modern data platforms, architecture, AI, machine learning, privacy, security, regulatory compliance, ethical data practices, executive stakeholder management, team leadership, change management, digital product prioritization, KPI definition, data literacy expansion, data architecture, integration, storage, platform modernization, talent development.
Preferred skills
External vendor and professional relationships across data, analytics, AI, and technology ecosystems.
Technologies
AI, Machine Learning, Security
Responsibilities
Define and execute the enterprise data, analytics, and AI strategy, roadmap, and investment plans; Assess organizational readiness and forecast data, infrastructure, and resource needs; Partner with executive and product leaders to prioritize initiatives and support digital products; Establish enterprise data governance, ownership, stewardship, security, privacy, and responsible AI practices; Lead data, analytics, and AI products from prioritization through ongoing enhancement; Define KPIs to measure business impact and promote continuous improvement; Expand self-service analytics, data literacy, and data-driven decision-making; Lead AI and machine learning solutions that automate processes and improve business outcomes; Guide data architecture, engineering, integration, storage, and platform modernization; Standardize key data domains and integration patterns to improve quality, scalability, interoperability, and performance; Build and lead teams across governance, data management, architecture, engineering, analytics, AI, and platform operations; Develop talent, career paths, performance standards, and training programs.