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Risant Health · 14 hours ago

Senior Analyst - Data Scientist (Hybrid - Washington, D.C.)

Washington, DC

Full-time

Hybrid

Senior Level

$143K/yr - $189K/yr

5+ years exp

Risant Health, a nonprofit affiliate of Kaiser Foundation Hospitals, is transforming healthcare by accelerating the adoption of value-based care across community health systems. The Senior Analyst / Data Scientist will translate complex data into actionable insights that drive value-based care and measurable results, leveraging modern data platforms and AI-driven methods. This role involves delivering high-quality analytics, collaborating with cross-functional teams, and ensuring operational excellence across Risant's portfolio.

Health CareHospitalNon Profit

Responsibilities

Deliver analytic products in short, iterative sprints - emphasizing speed to insight and incremental value creation

Partner with product, informatics, and operational leaders to define metrics of success, quantify impact, and align analytics with enterprise strategy

Use modern coding tools and platforms (Python, R, Databricks) to develop scalable analytics, predictive models, and automation pipelines

Apply AI-augmented analytics (e.g., generative summaries, intelligent outlier detection, next-best-action recommendations) to accelerate insight generation

Collaborate with informatics and engineering leaders to embed models and analytics into operational workflows and visualization tools

Build and evolve analytic capabilities that pinpoint cost drivers, impactable populations, and high-ROI opportunities across care settings. Translate advanced cost-of-care analysis into clear operational actions

Monitor and evaluate the performance and ROI of Risant’s value-based care platform, quantifying how initiatives and products deliver measurable value. Develop methods to continuously assess program performance, sustainability, and system-wide impact

Develop and maintain foundational analytic tools including advanced predictive models, segmentation logic, enrichment engines and vendor data pipelines to enable consistent, AI-ready insights across systems. Ensure these assets are versioned, validated, and integrated with enterprise EMR and product platforms for scalable use

Design and automate analytic pipelines, dashboards, and evaluation templates that make insights transparent, repeatable, and actionable. Build visualizations and reports that communicate value to leaders in clinical, operational, and financial domains

Contribute analytic templates, metric definitions, views and insights to the Risant Collaborative to drive shared learning and collective performance improvement

Implement automated data-quality checks and maintain clear documentation to ensure traceability and reliability of results

Maintain and approve semantic layers and analytic datasets that underpin enterprise reporting and insight generation

Work closely with cross-functional teams to ensure analytics translate into real-world decisions and measurable results

Present findings through concise narratives and visualizations that clearly connect data to value

Promote a culture of agile analytics, experimentation, and continuous improvement within the team and partner organizations

Qualification

Healthcare analyticsData science techniquesCloud-based data ecosystemsPredictive modelingPower BIAgile analytic deliveryAI-augmented analyticsCollaborationCommunication

Required

Bachelor's degree required in Data Science, Health Economics, Computer Science, Biostatistics, or a related quantitative or healthcare analytics field

Minimum of five (5) years of experience in healthcare analytics, health economics, or program evaluation, ideally within a payer, provider, or value-based care organization

Demonstrated experience using claims, administrative, and unstructured data sources to evaluate program performance, cost of care, and ROI

Experience developing in cloud-based data ecosystems and analytics pipelines (Azure Synapse, Databricks, Delta Lake) integrating claims, clinical, and unstructured data sources

Ability to create clear, high-impact visual summaries in modern visualization tools (e.g., Power BI)

Understanding of key healthcare payment models and metrics (TCOC, attribution, risk adjustment, utilization)

Familiarity with agile analytic delivery methods (sprints, backlog management, iterative delivery)

Familiarity with AI-augmented analytics tools (predictive modeling, generative summarization, automated segmentation) and the ability to apply them to real-world business use cases