Data Science & Analytics Strategy Leader

Leap Health; United States; Remote; USD 200,000 - 250,000; Full time

Job summary

Leap Health is seeking a Head of Data Science & Analytics to lead the data strategy, forecast demand, and measure impact across the business. You will own modeling, patient insights, and production analytics while partnering with Finance, Product, Clinical Operations, and Client Success.

You'll build scalable, explainable methods, manage a growing team of data scientists and analysts, and translate complex results into actionable guidance for clients and internal decision-making.

Qualifications

• Develop statistical or ML models that inform decisions and are used in operations.
• Strong foundations in statistics with experience in forecasting, causal inference, survival analysis or simulation.
• Experience with large healthcare datasets, claims or eligibility data, and data quality controls.
• Leading data science teams or building capability as an early hire with strong collaboration across functions.

Responsibilities

• Develop patient intelligence and predictive models using healthcare data.
• Forecast population demand and treatment volume across client populations.
• Establish rigorous methods to estimate savings, adherence, and access to care.
• Partner with Finance, Clinical Operations, Product, and Client Success to make methods reproducible and actionable.
• Lead and build the data science and analytics function, ensuring reproducibility and strong governance.
• Embed quality controls and documentation across data pipelines and analyses.

Skills

Statistical modeling

Machine learning

Healthcare data

Education

Advanced degree in statistics/biostatistics/computer science

Tools

dbt

Omni

Looker

Job description

Leap Health is seeking a Head of Data Science & Analytics to lead the data strategy, forecast demand, and measure impact across the business. You will own modeling, patient insights, and production analytics while partnering with Finance, Product, Clinical Operations, and Client Success.

You'll build scalable, explainable methods, manage a growing team of data scientists and analysts, and translate complex results into actionable guidance for clients and internal decision-making.