Health Plan Data Scientist

SCAN Medical Economics Analytics Team Member

Founded in 1977 as the Senior Care Action Network, SCAN began with a simple but radical idea: that older adults deserve to stay healthy and independent. That belief was championed by a group of community activists we still honor today as the "12 Angry Seniors." Their mission continues to guide everything we do.

Today, SCAN is a nonprofit health organization serving more than 500,000 people across Arizona, California, Nevada, New Mexico, Texas, and Washington, with over $8 billion in annual revenue. With nearly five decades of experience, we have built a distinctive, values-driven platform dedicated to improving care for older adults.

Our work spans Medicare Advantage, fully integrated care models, primary care, care for the most medically and socially complex populations, and next-generation care delivery models. Across all of this, we are united by a shared commitment: combining compassion with discipline, innovation with stewardship, and growth with integrity.

At SCAN, we believe scale should strengthen—not dilute—our mission. We are building the future of care for older adults, grounded in purpose, accountability, and respect for the people and communities we serve.

The Job

This role will be a key member of SCAN's Medical Economics Analytics team, responsible for identifying, quantifying, and helping capture total cost of care (TCOC) savings opportunities across the health plan's core medical cost management levers: clinical programs, utilization management (UM) and medical policy, payment integrity, network and contracting, benefit design, coordination of benefits (COB), and supplemental programs. The role combines strong health plan operations knowledge with data science methods and AI-enabled analytics tooling (GenAI, agentic workflows) to surface and size opportunities from claims, clinical, and contract data.

This role will collaborate with clinical, network, payment integrity, and finance stakeholders to convert analytic findings into total cost of care strategy, in support of SCAN's mission of keeping seniors healthy and independent.

You Will

1. Apply data science and analytical methods (such as segmentation, trend analysis, statistical modeling, and GenAI-enabled synthesis) to claims, clinical, and contract data to identify, size, and prioritize total cost of care (TCOC) savings opportunities across SCAN's core medical cost management levers. Illustrative examples could include:

• Utilization management (UM) and medical policy: evaluating program effectiveness, medical policy application and exception patterns, and utilization outliers
• Payment integrity: identifying claims coding, billing, and payment accuracy opportunities (e.g., DRG validation, upcoding, duplicate payment, coordination of benefits recovery)
• Network and contracting: analyzing unit cost, provider relativity, and site-of-service shift to inform contracting strategy
• Benefit design and coordination of benefits (COB): evaluating benefit changes and COB recovery opportunities for cost and member impact
• Supplemental programs: assessing utilization, cost, and return on investment
• Clinical programs: building segmentation and predictive models to prioritize cost management interventions
• AI-enabled synthesis: applying GenAI and agentic AI tools to synthesize claims, clinical, and contract data and accelerate opportunity identification

2. Leverage strong health plan operations knowledge and business acumen to identify and prioritize total cost of care opportunities based on SCAN's highest-value medical cost management levers

3. Create requirements, test and validate analyses, communicate findings and savings opportunity sizing to Medical Economics, Finance, Network, and Clinical business partners, and support opportunity tracking through implementation.

4. Help shape and implement SCAN's medical economics analytics and AI strategy in coordination with key stakeholders across the company. Manage multiple projects at a time based on the priorities and delivery methodologies of the Medical Economics Analytics team, while also being a mentor to other analytics practitioners.

Your Qualifications

• Bachelors Degree in statistics, mathematics, computer science, or related field required
• Graduate or Advanced Degree in statistics, mathematics, computer science, or related field required
• 3+ years working experience, preferably including healthcare industry experience
• 3+ years applying data science and analytical methods (e.g., statistical modeling, segmentation, trend analysis, machine learning, GenAI/agentic AI) to identify and quantify business or medical cost opportunities
• 1+ years of experience writing SQL code in relational database environment
• 2+ years of experience writing code in Python and/or R
• Experience with Snowflake and/or Databricks as well as Power BI.
• Experience with Streamlit or other data as a service apps, preferred
• Working knowledge of GenAI/LLM tools for synthesizing structured and unstructured health plan data…