Healthcare Data Scientist

Diverge Health is dedicated to improving health access and outcomes for underserved populations. The Healthcare Data Scientist will enhance analytics capabilities and convert complex healthcare data into actionable insights, collaborating with various teams to support data-driven decisions that improve patient outcomes.

Responsibilities:

• Analyze healthcare datasets—including claims, electronic health records, and health information exchange data—to identify opportunities to improve patient care and outcomes
• Develop models and analytical approaches to support population health initiatives such as risk stratification, quality improvement, and market analysis
• Design and deliver dashboards, reports, and data visualizations that translate complex findings into clear, actionable insights
• Partner with clinical, operational, and leadership teams to define analytics needs and guide data-informed decisions
• Build and maintain data models and analytical workflows using tools such as Snowflake, DBT, and modern cloud data platforms
• Apply statistical methods and advanced SQL techniques to investigate trends, evaluate programs, and inform strategy
• Explore and integrate new data sources—including population, census, and operational data—to deepen understanding of patient needs
• Contribute to the evolution of our analytics infrastructure and machine learning capabilities using cloud-based tools and notebooks
• Stay current with emerging AI technologies and contribute to strategic roadmap planning

Requirements:

• 3–8 years of experience in healthcare data science, analytics, or related field
• Strong experience working with medical claims data, including familiarity with healthcare billing, reimbursement, and coding structures
• Advanced proficiency in SQL, statistical analysis, and healthcare data modeling
• Experience building dashboards and reports using BI tools such as Sigma, Salesforce reporting, or similar platforms
• Familiarity with modern data infrastructure and cloud platforms (e.g., Snowflake, AWS, DBT, or comparable technologies)
• Experience with AI/ML workflows, Jupyter notebooks, or SageMaker
• Ability to clearly communicate analytical insights to both technical and non-technical audiences
• Demonstrated curiosity and ability to learn new tools and technologies quickly
• Familiarity with LLMs and prompt engineering for real-world applications
• Experience analyzing healthcare quality metrics such as HEDIS or STARS
• Experience building or automating data and machine learning pipelines
• Broad experience across analytics infrastructure, visualization, statistics, and data engineering in healthcare environments