Director of Data, Analytics, and AI

Are you passionate about shaping the future of data, analytics, and artificial intelligence in a business-critical environment? MEM Insurance is seeking a visionary Director of Data, Analytics & AI to lead our enterprise data strategy, analytics capabilities, and AI/ML practice. In this highly visible leadership role, you will partner with executive and operational leaders across the organization to transform business priorities into data-driven solutions that create measurable impact.

As the leader of MEM 's data and AI function, you will establish the strategy, governance, platforms, and practices that enable trusted decision-making across the enterprise. You will oversee the development of scalable data foundations, advanced analytics capabilities, and responsible AI initiatives while ensuring compliance within a regulated insurance environment. This role offers the opportunity to influence enterprise strategy, drive innovation, build high-performing teams, and help define how data and AI will shape the future of MEM Insurance.

Essential Duties and Responsibilities Enterprise Strategy & Leadership

- Own and continuously evolve MEM 's enterprise data, analytics, and AI strategy to align with business priorities, organizational goals, and risk management requirements.

- Partner with Product Management and business leaders to understand strategic objectives and translate them into actionable data, analytics, and AI roadmaps.

- Establish the long-term vision for data platforms, analytics environments, and AI/ML infrastructure, including build, buy, and partner decisions.

- Identify and evaluate emerging AI capabilities and prioritize investments based on business value, organizational readiness, and risk-adjusted returns.

- Maintain executive-level engagement through transparent communication of portfolio outcomes, delivery progress, and risk considerations.

AI & Analytics Leadership

- Lead the organization's AI/ML practice, ensuring solutions are reliable, scalable, and deliver measurable business outcomes.

- Establish enterprise standards for model development, validation, deployment, monitoring, and retirement.

- Guide the evaluation, piloting, and deployment of generative AI and emerging AI technologies while balancing innovation with responsible governance.

- Promote enterprise adoption of AI-enabled tools and opportunities that improve effectiveness, efficiency, and decision-making.

- Define and oversee operational practices for machine learning including model management, monitoring, observability, and lifecycle governance.

Data Foundation & Architecture

- Direct enterprise data architecture and data platform strategies that support analytics, AI, and operational business needs.

- Ensure data engineering practices deliver high-quality, trusted, well-documented, and scalable data assets.

- Partner with technology and operational leaders to maintain a unified data ecosystem that supports future growth and innovation.

- Champion user-centered design with a strong focus on the usability and accessibility of analytics and data products.

Governance, Risk & Responsible AI

- Lead enterprise data governance efforts, including data quality, lineage, stewardship, access controls, retention practices, and business glossaries.

- Oversee the AI governance framework including model inventories, risk classification, validation standards, monitoring, explainability, and fairness assessments.

- Ensure data and AI initiatives comply with applicable insurance regulations, emerging AI requirements, and internal governance standards.

- Partner with Legal, Compliance, Risk, and other stakeholders to translate regulatory expectations into practical operational controls.

- Identify and proactively manage technical, operational, regulatory, and reputational risks associated with data and AI initiatives.

Business Partnership & Delivery

- Partner with leaders across underwriting, claims, actuarial, safety and risk serv