About Leap

Leap is one of the fastest-growing benefits solutions and a category-defining pioneer in employer specialty pharmacy. We are reshaping how life-changing therapies are delivered and financed, ensuring patients get the treatment they need while employers finally get a fair deal.

Specialty drugs and infusions represent nearly 10% of all healthcare spend and are the fastest-growing cost category for employers. Leap tackles this challenge with a novel approach: eliminating hidden markups, expanding access to high-quality infusion providers, and bringing clarity and fairness to how therapies are priced and paid for.

We’re proud to partner with numerous Fortune 500 companies and leading TPAs. Each patient we serve creates immediate ROI: lower costs, improved access, and better care. Join us as we redefine what’s possible in specialty care.

About the Role

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.

This is a hands-on leadership role with room to build a team and shape the function. It reports to Leap’s President and co-founder.

Key Responsibilities

Develop Patient Intelligence and Predictive Models

Develop methods for identifying patients who may benefit from Leap using medical and pharmacy claims, eligibility records, clinical information, and operational data.

Translate incomplete and fragmented observations into useful signals about therapy utilization, treatment status, care transitions, and opportunities for engagement.

Develop and validate models of patient engagement, treatment initiation, adherence, and persistence, with clear definitions of what the available data can reliably establish.

Evaluate models for accuracy, calibration, bias, and operational usefulness, accounting for missing data, claims lag, and differences across populations.

Partner with Engineering, Product, and Clinical Operations to bring validated methods into production workflows and monitor their performance over time.

Forecast Population Behavior and Demand

Build population-level models that connect covered lives to specialty therapy utilization, serviceable members, active patients, and treatment volume.

Account for stochastic variation, sparse observations, population differences, and the outsized effect of individual patients and high-cost therapies.