VP, Head of AI

About PURE Insurance

PURE Insurance is actively investing in our data, analytics, data science, machine learning (ML), and artificial intelligence (AI) capabilities. We are building a centralized Data & AI department that brings together specialists across data architecture, engineering, analytics, governance, and advanced modeling. This structure provides extraordinary opportunities for growth, collaboration, and innovation across every function of the insurance ecosystem, from Claims and Underwriting to Actuarial, Product, Distribution, Finance, and more.

We work with a modern data technology stack that includes Databricks, dbt, GitHub, Hex, and Arize, while also developing in-house production-grade software in Python and other languages when it provides a competitive edge. At PURE, we embrace curiosity, craftsmanship, and a relentless pursuit of improvement. Our culture values growth, mentorship, transparency, and ownership, and we know that building a strong foundation takes time and a willingness to experiment, learn, and adapt.

The Role: VP, Head of AI

PURE Insurance is seeking a Vice President, Head of AI to establish and lead our enterprise AI/GenAI strategy and execution. Reporting to the Chief Data & Analytics Officer, this leader will oversee Data Science, AI engineering, and MLOps teams, ensuring seamless collaboration to deliver production-ready, high-impact solutions.

This is a rare opportunity to shape how AI transforms the P&C insurance industry. The Head of AI will:

• Lead, grow, and foster a culture of innovation, accountability, safe experimentation, and continuous learning across three core teams: Data Science, MLOps Engineering, and a new AI Engineering team (3 initial hires).
• Partner with executive leadership to prioritize and roadmap high-impact AI/GenAI initiatives, balancing pragmatic near-term opportunities with longer-term "moonshot" innovations.
• Engage senior leaders to frame business problems, champion transformative possibilities, and ensure AI initiatives align with enterprise priorities.
• Shape PURE's long-term philosophy on building vs. buying AI solutions, balancing cost, scalability, speed, and strategic value.
• Ensure data science and automation approaches are fully leveraged where they are the right solution, recognizing that not every problem requires AI.
• Collaborate with IT, Technology, Data Engineering, and Analytics Engineering teams to ensure that PURE's data and source systems can support AI solutions in a scalable and pragmatic way.
• Lead PURE's commitment to ethical and responsible AI, ensuring transparency, fairness, and trust in every solution we deliver.
• Anticipate and navigate evolving regulatory considerations for AI in insurance, ensuring PURE stays ahead of compliance requirements.
• Work with change management experts to drive enterprise-wide adoption, ensuring AI solutions are understood, trusted, and embedded into workflows that elevate performance.
• Define and track key performance metrics to measure the business value and ROI delivered by data science and AI initiatives, and communicate results effectively to senior leadership.
• Foster a sustainable talent pipeline by defining career paths, supporting professional development, and ensuring succession planning across Data Science, AI Engineering, and MLOps/AIOps Engineering teams.
• Stay at the forefront of emerging AI trends, infuse fresh insights into PURE's strategy, and represent the company as an industry thought leader.

The Ideal Candidate

We are seeking a rare blend of strategist, technologist, and changemaker. The ideal candidate will bring:

• Bachelor's degree in Computer Science, Mathematics, Engineering, or related field; advanced degree preferred.
• 10+ years of experience in data science, machine learning, and AI, with increasing responsibility over time and at least 3 years in a senior leadership role, including hands-on expertise with predictive modeling, deep learning, NLP, computer vision, or time-series analysis.
• Experience with generative and agentic AI, including deploying real-world use cases into production.
• Skilled at leading and mentoring multidisciplinary teams, uniting data scientists, ML/AI engineers, and MLOps engineers to deliver at scale.
• Proven ability to deliver MVPs quickly, manage technical debt wisely, and scale solutions responsibly.
• Familiarity with P&C insurance or financial services is highly desirable, but the ability to bring fresh ideas from other industries and challenge legacy assumptions is equally important.
• Strong appreciation for organizational change management and the human side of adoption, ensuring that technology enhances workflows rather than causing disruption.
• Experience making build vs. buy decisions, balancing short-term needs with long-term strategic priorities.
• Adaptability with technology: not tied to specific tools but skilled at discerning when a platform is an asset versus a liability.
• Demonstrated ability to measure and communicate business value, tying data science and ML/AI outcomes to enterprise objectives.
• A collaborative and customer-first leader whose success comes from building solutions that deliver lasting value for PURE's members, brokers, and employees.

Why Join PURE

• Be at the forefront of transforming P&C insurance through AI and GenAI.
• Lead three specialized teams (Data Science, AI Engineering, and MLOps/AIOps Engineering) within a supportive, well-funded, and forward-thinking organization.
• Work in a culture that values curiosity, collaboration, responsibility, and continuous learning.
• Enjoy the flexibility of a remote role with the option to work in PURE offices in major U.S. cities.
• Shape the future of AI in insurance by defining what excellence looks like for a next-generation carrier and elevating PURE's reputation as an industry innovator.

The base salary for this role can range from $225,000 to $275,000 based on a full-time work schedule. An individual's ultimate compensation will vary depending on job-related skills and experience, geographic location, alignment with market data, and equity among other team members with comparable experience

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