Head of Data & AI

Overview

Founded in 1898, Mutual of Enumclaw is a people-first insurer rooted in community, recognized as Washington’s Best Company to Work For for the 14th consecutive year, and proudly serving individuals, families, farms, and businesses through local independent agents across the West.

The Head of Data & AI is MOE's enterprise leader for data and artificial intelligence. This is a strategy and execution role, not a research role: you set the vision, decide where MOE should buy, partner, or build, and put AI into real underwriting, claims, and distribution workflows.

MOE takes a buy-first approach to AI today. Much of your impact will come from choosing the right partners, connecting their solutions to our data and core systems, and driving adoption. Sometimes the best answer will be better data or simple automation, not AI.

Location: Onsite - Seattle, WA (relocation assistance is available for qualified candidates.)

Hiring Range: $207,700 - $230,500*

Salary Range: $207,700 - $257,600

*The Hiring Range represents Mutual of Enumclaw’s current hiring pay scale for this role. Mutual of Enumclaw reserves the right to modify or update this range any time. Exact compensation may vary based on skills and experience. Compensation is only one part of our entire total rewards package. To see some of the benefits and perks we offer, please click here.

Responsibilities

Strategy and Roadmap

• Define and own MOE's enterprise data and AI strategy, aligned with business objectives and the technology modernization roadmap.
• Build a prioritized portfolio of AI use cases across underwriting, claims, pricing, agency distribution, and operations, balancing near-term wins with longer-term transformation.
• Set MOE's build, buy, and partner philosophy, weighing cost, speed, scalability, risk, and strategic value.

Vendor and Partner Leadership

• Identify, evaluate, and select AI, data, and insurtech vendors; lead due diligence on performance, data handling, security, and explainability.
• Negotiate contracts and manage third-party AI relationships, including audit rights, data ownership, and performance commitments.
• Manage the vendor portfolio to prevent overlapping tools and ensure solutions integrate with MOE's platforms.

Data Foundation

• Lead the modern data platform – Medallion Architecture as part of MOE's cloud transition: ingestion, quality, master data, lineage, and accessibility. Partner with Data analytics and reporting team in supporting business insights need.
• Partner with the Enterprise Architect so data and AI capabilities fit MOE's target architecture and API strategy.
• Establish data governance and ownership across business domains, so the data feeding AI is accurate, permissioned, and traceable.

Responsible AI and Regulatory Readiness

• Establish and run MOE's AI governance framework: AI inventory, risk tiering, bias and fairness testing, explainability, monitoring of vendor and internal AI, and documentation.
• Anticipate evolving AI regulation in insurance and keep MOE ahead of state Department of Insurance and NAIC expectations, with Legal, Compliance, and Risk.
• Set acceptable-use standards for generative AI tools across the company.

Adoption and Value

• Partner with business leaders and change management to embed AI into everyday workflows, so solutions are understood, trusted, and used.
• Lead AI literacy and enablement programs, including a network of AI champions across departments.
• Define and report KPIs showing the business value and ROI of data and AI investments to executive leadership and the Board.

Team and Talent

• Build a lean, high-impact team: hire selectively for scarce skills and create reskilling paths, such as BI developers to analytics engineers and business analysts to AI product owners.
• Define career paths and succession across data and AI roles.
• Represent MOE as a thoughtful voice on AI in regional P&C insurance.

Supervisory

• Recruit, onboard, and manage the Data & AI team.
• Set individual development goals for direct reports and identify successors for key data and AI positions.
• Perform assessment of employee performance.

Qualifications

Required Skills/Abilities

• Bachelor's degree in Computer Science, Data Science, Statistics, Information Systems, Business, or a related field, or equivalent experience.
• 12+ years in data or AI, including 5+ years leading teams and enterprise programs.
• A proven record of delivering AI into production with measurable business results, including through vendor or partner-delivered solutions.
• Experience making build-versus-buy decisions and managing strategic technology vendors and contracts.
• Hands-on experience establishing data governance and responsible AI or model risk practices in a regulated industry.
• Working knowledge of modern cloud data platforms and of generative and agentic AI, including their risks and controls. You can tell when a platform is an asset and when it's a liability.
• Strong change leadership: you know adoption, not technology, usually determines ROI.
• Executive presence and the ability to explain AI clearly to the executives, board, regulators, agents, and frontline teams.

Strongly Preferred

• P&C insurance experience, especially in underwriting, claims, pricing, or agency distribution.
• Experience working with actuarial teams and insurance regulators.
• Experience leading data and AI work during cloud migration or core system modernization.

What Success Looks Like in the First 12 Months

• Business leadership endorsed data and AI strategy, with a prioritized use-case portfolio and a build, buy, and partner framework.
• An AI governance framework and enterprise AI inventory in place, covering vendor and internal AI.
• 2-3 AI solutions live in production, with tracked business outcomes.
• A data foundation roadmap aligned with cloud migration, with measurable data quality improvement in priority domains.
• An AI enablement program launched, with champions in each major department.
• A core team in place, combining targeted hires and internal reskilling.

Physical Requirements

• Prolonged periods of sitting at a desk and working on a computer, including video conferencing.
• Lifting of 15 lbs.