Head of Data Science & Analytics

The posting, as Leap wrote it

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 meth

[…]
al or Bayesian modeling, forecasting, survival analysis, causal inference, or simulation. You know how to choose an approach that fits the data and the decision.

• You’ve worked hands-on with large healthcare datasets, including claims or eligibility data, and understand their coding, timing, completeness, and interpretation challenges.
• You’ve worked with functional leaders to define how outcomes and performance are measured, built a roadmap from their most important questions, and delivered the models, reporting, and quality controls that put it into use.
• You’ve led data scientists or analysts, or built a substantial capability as an early technical hire, and want to remain close to the work.
• You use AI tools effectively while maintaining independent judgment, reproducibility, and appropriate validation.

PREFERRED

• Experience in specialty pharmacy, payer, PBM, actuarial, health benefits, or clinical outcomes analytics.
• Experience identifying patient cohorts or treatment patterns from longitudinal healthcare data.
• Experience measuring healthcare costs, adherence, or program impact using experimental or observational methods.
• Experience forecasting low-frequency, high-cost events or heterogeneous populations with limited historical data.
• Experience with analytical data modeling, semantic layers, and self-service reporting tools such as dbt, Omni, or Looker.
• An advanced degree in statistics, biostatistics, computer science, applied mathematics, economics, epidemiology, or a related quantitative field, or equivalent applied experience.
• Experience building in a fast-growing company.

At Leap, we’re building an outlier company with real impact — and that takes focus, energy, and commitment. If that excites you, we’d love to hear from you.

Leap is an equal opportunity employer and welcomes applicants from all backgrounds. We’re committed to building a team that reflects a diversity of perspectives, experiences, and identities.