AVP, Data Science

At Met Life, data isn’t just a tool – it is a catalyst for growth. As part of our Data & Analytics organization, you’ll unlock trusted insights that drive bold decisions, power personalized customer experiences, and deliver lasting business impact. We’re building the future of data – one that’s governed responsibly, engineered for scalability, and designed for growth. When you join us, you’re not just supporting the business – you’re empowering it.

Let’s transform insight into impact and data into action, together.

The AVP, Data Science is a senior leader within Met Life’s Enterprise Data Science & AI function, reporting to the Head of Data Science & AI, and is responsible for driving the delivery and enterprise adoption of data science, machine learning (ML), and generative AI solutions across the company’s global businesses and functions. The AVP oversees two areas, Applied Data Science and Enterprise AI Capabilities, and leads a team of 6–8 data scientists and ML engineers.

The AVP partners with business leaders and regional data officers to identify and deliver high-value use cases that support growth, profitability, and operational efficiency, and ensures solutions scale beyond pilots into production, where they are adopted and monitored. In parallel, the AVP builds reusable, production-grade AI capabilities, with the standards and practices that help regions move faster, with more consistency and quality, working closely with data engineering, technology, risk, and governance partners.

Met Life has a strong foundation in data science and a clear opportunity to turn it into enterprise-wide impact. The AVP is a change leader as much as a technical leader: a hands‑on expert in statistical modeling, ML, and generative AI who earns credibility with experienced data scientists and regional leaders, leads through influence in a federated, global organization, and brings a product mindset focused on user experience and tangible business impact.

The AVP balances innovation and creative problem solving with operational rigor and responsible AI in a regulated environment.

• Lead the delivery of data science, ML, and AI solutions across key business areas, from problem definition through deployment and ongoing performance monitoring, with accountability for adoption and measurable business impact.
• Partner with business leaders and regional data officers to identify, prioritize, and execute high-impact AI use cases tied to growth, profitability, and operational efficiency.
• Apply a product approach to AI solutions: define users, adoption, and value measures up front, deliver a strong user experience, and ensure solutions are used, supported, and improved after launch.
• Apply advanced statistical modeling, ML, and generative AI techniques to complex business problems, choosing the right method for each decision and translating insights into clear, actionable recommendations.
• Drive experimentation and innovation through pilots and proofs of value, with a clear path to scale successful solutions across the enterprise or stop those that do not earn adoption.
• Collaborate with data engineering, technology, and platform teams to build and scale enterprise-grade MLOps / AIOps capabilities, including model development, deployment, and monitoring.
• Promote the reuse and standardization of models, data assets, and AI components across regions and teams to improve speed, consistency, and quality.
• Contribute to the Data Science & AI Center of Excellence and communities of practice: share best practices, standards, and reusable tools, and encourage knowledge sharing and adoption of modern approaches across regions.
• Partner with risk, legal, and governance teams so that AI…