Director of Data & AI

Director of Data & AI
About the Role

We are seeking a visionary and strategic Director of Data and AI to establish and lead our organization’s dedicated data and artificial intelligence function. This is a transformational leadership opportunity to build enterprise-wide data and AI capabilities that drive innovation, efficiency, and competitive advantage. Reporting directly to the Chief Information Officer, this leader will be responsible for developing the company’s data ecosystem, implementing scalable AI solutions, and creating the organizational foundation for becoming a truly data-driven business.

Key Responsibilities

Strategic Leadership & Vision

• Develop and execute a comprehensive data and AI strategy aligned with the organization’s long-term objectives and regulatory obligations.

• Champion a data-driven culture across teams, serving as a strategic advisor and thought leader on data and AI initiatives.

• Establish enterprise-wide governance frameworks, policies, and standards for data management, quality, and ethical AI practices.

• Partner with senior leadership to identify high-impact opportunities where data and AI can accelerate business performance.

• Define and communicate the strategic roadmap for data infrastructure, analytics capabilities, and AI maturity.

Data Ecosystem Development

• Design and implement a scalable, secure data architecture supporting analytics, AI/ML, and business intelligence use cases.

• Build and maintain governance frameworks for data quality, metadata management, and data lineage.

• Implement master data management (MDM) and data integration strategies across complex business systems.

• Develop modern data lake/lakehouse and warehouse solutions optimized for both operational and analytical workloads.

• Ensure compliance with global data privacy and security regulations (GDPR, CCPA, etc.).

• Build self-service data discovery and cataloging capabilities to enable enterprise-wide access to trusted data.

AI & Advanced Analytics

• Identify, prioritize, and deliver AI and ML initiatives that produce measurable business value.

• Develop responsible AI frameworks addressing bias mitigation, model transparency, and ethical risk management.

• Establish MLOps standards for model development, deployment, and lifecycle management.

• Enable predictive and prescriptive analytics to support use cases such as risk assessment, customer insights, and operational optimization.

• Evaluate emerging generative AI technologies and lead proof-of-concept initiatives where appropriate.

Team Building & Leadership

• Build, mentor, and lead a multidisciplinary team of data engineers, analysts, data scientists, and AI specialists.

• Define clear roles, responsibilities, and growth paths within the data and AI organization.

• Foster a culture of innovation, collaboration, and technical excellence.

• Develop external partnerships with universities, technology vendors, and research organizations to attract talent and stay ahead of emerging trends.

• Promote data literacy and AI education programs across the enterprise.

Stakeholder Management & Collaboration

• Collaborate with business leaders to translate strategic needs into actionable data and AI solutions.

• Partner closely with technology, security, compliance, and risk functions to ensure alignment and integration.

• Manage relationships with technology vendors, consultants, and external partners.

• Present updates and strategic insights to executive leadership and relevant committees.

• Act as the organizational point of contact for data and AI governance discussions with external stakeholders.

Technology & Infrastructure

• Oversee selection and implementation of modern data platforms, tools, and technologies.

• Ensure infrastructure scalability, reliability, and cost-effectiveness across on-premise and cloud environments.

• Define and execute a cloud data strategy and hybrid architecture where appropriate.

• Implement real-time and streaming data capabilities to support high-velocity use cases.

• Oversee API development for data sharing and system integration.

Required Qualifications

Education & Experience

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field; Master’s degree or MBA preferred.

• 10+ years of progressive experience across data management, analytics, or AI/ML disciplines.

• 5+ years in senior leadership roles with experience building and scaling data or analytics teams.

• Background in a complex, regulated, or data-intensive industry strongly preferred.

• Demonstrated success establishing a data and analytics function from inception to maturity.

Technical Expertise

• Deep understanding of modern data architecture patterns (data lakes, lakehouses, data mesh, etc.).

• Strong command of data governance, quality management, and MDM practices.

• Expertise in AI/ML techniques including NLP, predictive modeling, and generative AI.

• Proficiency with cloud platforms (AWS, Azure, or GCP) and their data/AI ecosystems.

• Experience with ETL/ELT processes, DataOps, and MLOps frameworks.

• Familiarity with data visualization and BI tools for enterprise analytics.

Business & Leadership Skills

• Strategic mindset with the ability to connect data initiatives to business outcomes.

• Exceptional communication skills and the ability to influence at all organizational levels.

• Proven ability to drive cultural and operational transformation through data.

• Strong project and program management capabilities.

• Financial literacy and experience developing ROI-driven business cases for data investments.

Industry Knowledge

• Experience working within a highly regulated or compliance-driven industry environment.

• Understanding of data privacy, security, and ethical AI standards.

• Awareness of trends in digital transformation, AI innovation, and data-driven business models.