Director, Chief Data & Advanced Analytics Officer

Overview

Reporting to the Vice President & Chief Information & Technology Officer, the Director, Chief Data & Advanced Analytics Officer (Director) leads the corporation’s data, analytics, and artificial intelligence (AI) strategy to drive business value and enable a data‑driven culture.

The position is accountable for establishing the enterprise data and analytics operating model, governing and managing data assets, advancing analytics and AI capabilities, and developing high‑performing data talent. The role leads a team of data professionals focused on delivering strategic and operational insights through trusted, high‑quality data.

Working closely with cross‑functional leaders, the Director identifies data and AI opportunities, designs analytics solutions, and provides actionable insights to improve decision‑making, growth, and efficiency. As a visible change agent, the Director champions best practices in data governance, analytics, and responsible AI adoption across the organization.

ResponsibilitiesData and Analytics Strategy & Stakeholder Relations:

• Accountable for defining and executing the enterprise data, analytics, and AI strategy, aligned with business priorities to deliver measurable value.
• Establish and lead the corporate Data and Information Governance program, ensuring effective policies, standards, and oversight through an Enterprise Data Governance Council.
• Ensure optimal and strategic use of data and analytics by actively shaping future data and analytics capabilities and investment priorities.
• Champion a data‑driven culture by building data and AI literacy, behaviors, and competencies across the enterprise, while developing Data & Analytics talent and maturity.
• Set the vision, outcomes, and success measures for data, analytics, and AI in partnership with executive and senior leaders.
• Design and implement the data, analytics, and AI operating model, including architecture, ecosystem, and delivery approach.
• Partner with executive leadership and the Board to manage data as a strategic asset, ensure AI‑readiness, and communicate the business value realized from data, analytics, and AI initiatives.

Data Management & Operations:

• Accountable for the end‑to‑end management of corporate data, including data platforms, engineering practices, processing solutions, and business intelligence applications.
• Define and maintain enterprise data architecture, models, and secure, efficient data pipelines to ensure reliable, AI‑ready data across the organization.
• Establish and evolve data science, advanced analytics, and AI capabilities, including leadership of a Data & Analytics Centre of Excellence.
• Maintain authority over data assets, analytics, and AI‑enabled decision solutions by instituting strong governance, stewardship, and collaboration with security, privacy, risk, and compliance leaders.
• Oversee enterprise delivery models, methods, and standards for data, analytics, and AI solutions, including centralized data product and engineering services.
• Lead the evolution of Data & Analytics technology in partnership with the Chief Information & Technology Officer, including vendor strategy, platform roadmaps, and alignment with enterprise IT policies.

Regulatory & Governance:

• Lead enterprise data and analytics compliance programs, represent the organization with regulators and external bodies, and ensure audit readiness for all data supporting regulatory and financial reporting.
• Establish and chair data governance committees; define enterprise data principles, stewardship, trust models, and controls for master data, metadata, and data quality to ensure consistency, traceability, and reliability.
• Ensure that controlled data and analytics accurately reflect the true state of the business and support legal, financial, and management reporting requirements.
• Oversee the ethical use of data, analytics, and AI‑enabled decision‑making, ensuring privacy protection, responsible algorithms, and practices that exceed regulatory expectations.

QualificationsEducation:

• Degree in Business Administration, Computer Science, Science Technology, Engineering, Information Systems, Statistics, Mathematics or related discipline.
• Post-graduate degree in a related discipline is an asset.
• Industry certification related to data (such as DAMA-DMBOK2) is an asset.
• Project Management Professional (PMP) is an asset.

Experience:

• Ten years of senior level experience in business management, legal, financial or information or IT management, including:

1. Five years at a senior management level.
2. Five years of progressive leadership experience in leading cross-functional teams, multidisciplinary environments and enterprise-wide data and analytics programs, operating and influencing effectively across the organization and within complex contexts.
3. Experience in integrating complex, cross-corporate processes and information strategies, and/or designing strategic metrics and scorecards.

• Broad business experience internally and within the insurance industry, as well as strategy and management consulting experience is an asset.

Technical Knowledge and Skills:

• Strong acumen for strategic business and technology planning and execution, including policy development and maintenance. In some cases, contribute to the AI strategy.
• Broad understanding of the full range of strategic data and analytics capabilities and the ability to communicate these concepts, methods and techniques in ways easily understood by other stakeholders.
• Advanced knowledge of information systems/tools, related software and data management, enterprise content management, and record-keeping policies and practices in a complex organizational environment.
• Advanced knowledge of enterprise application and data architecture principles, and associated tools, technologies and methods as it relates to the solutioning of data-driven initiatives which align with enterprise standards, vision and strategy.
• Advanced knowledge to build data analytics and management capabilities from inception with exposure to cloud technologies offered by Microsoft, Google, and Amazon.
• Proven capabilities in migrating data warehouse capabilities from on premises to cloud platforms and building AI/ML and automation capabilities.
• Exceptional oral and written communication skills to clearly convey complex information in a concise and straightforward manner.
• Excellent interpersonal skills, with experience of superior performance in public speaking and formal presentations.