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

Risant Health•Washington, DC

2d•$142,917 - $188,650•Hybrid

About The Position

Risant Health, a nonprofit affiliate of Kaiser Foundation Hospitals, is transforming healthcare by accelerating the adoption of value-based care across community health systems. Headquartered in the Washington, DC area, Risant Health partners with nonprofit, community-based systems—starting with Geisinger—to expand access to care that prioritizes health outcomes and affordability. Backed by nearly 80 years of Kaiser Permanente’s value-based care expertise, Risant Health operates independently to support its portfolio of health systems with shared resources, strategic guidance, and operational support—while preserving their community roots. The Data & Analytics team turns complex health and financial data into clear, actionable intelligence that drives strategic, operational and clinical decision-making across Risant’s portfolio. In this role, you’ll use structured and unstructured data sources to deliver high-quality analytics aligned with key business priorities - evaluating programs, surfacing high-ROI opportunities, and creating advanced analytics solutions. The team provides strategic guidance, fosters cross-functional collaboration, and ensures excellence across every engagement—driving innovation, efficiency, and quality in healthcare delivery. Role Summary The Senior Analyst / Data Scientist plays a vital role in translating complex data into actionable insights that drive value-based care and measurable results. This role bridges analytics, product, operations and informatics - leveraging modern data platforms, agile tools, and AI-driven methods to deliver insights that improve affordability, outcomes, and performance across Risant Health’s community-based systems. The analyst applies statistical and economic methods to monitor key trends, routinely surface performance improvement opportunities, evaluate programs and products, quantify impact, and support embedded analytics for clinical users and informatics teams. You’ll apply your knowledge of healthcare data, modern data science techniques, and value based care to translate insight into measurable value. This role blends rigorous quantitative analysis with agile, AI-driven methods to accelerate time to impact, guiding reinvestment in what works and advancing value-based care across the Risant Health enterprise.

Requirements

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.

Nice To Haves

Master’s degree preferred (e.g., MPH, MS in Data Science, Health Informatics, or Applied Analytics).

Responsibilities

Analytics Delivery & Value Creation 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.
Foundational, Predictive & Performance Analytics Medical Cost Analytics: 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.
Program & Platform Evaluation: 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.
Core Analytic Assets: 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.
Data Pipelines, Visualizations & Business Artifacts: 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.
Data Stewardship & Collaboration 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.
Collaboration & Communication 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.