Head of Data Science & Analytics

How do you identify patients who could benefit from specialty care support within broad, imperfect healthcare datasets? How do you forecast treatment demand across populations where a small number of patients can drive substantial variation? How do you reliably estimate the savings and impact of a care model when claims arrive late, treatment patterns change, and the alternative course of care isn’t always directly observed?

As Head of Data Science & Analytics, you’ll lead Leap’s work on these questions. You’ll develop the methods and models that help us identify patients, anticipate their needs, forecast population behavior, and measure our effect on costs, adherence, and access to care. Your work will directly inform how we engage members, support clients, source therapies, and invest in the business.

Our team has built a solid foundation across data engineering, analytics, and operational reporting. This role builds on that work, bringing dedicated data science and analytical leadership to substantially expand our capabilities. You’ll develop new ways to predict what comes next, evaluate which analytical models are effective, and apply those insights across a rapidly growing business.

You’ll partner directly with leaders across Finance, Commercial Growth, Client Success, Pharmacy, Clinical Operations, and Product to answer complex analytical questions that shape our strategy and strengthen the operational reporting they use to run their teams. Building on our existing infrastructure, you’ll work with data engineering and analytics colleagues to strengthen shared metrics, expand reporting capabilities, and embed quality controls that keep our numbers reliable as Leap scales. You’ll own a cross-functional roadmap that connects these investments to business priorities, giving every team a clear view of performance and the analytical tools to improve it.

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