Lead Risk Adjustment Informatics & Analytics

CVS Health; United States; Remote; USD 66,000 - 146,000; Full time

Benefits offered by this job

Bonus eligible

Job summary

CVS Health seeks an experienced analytics professional to drive risk adjustment valuation initiatives and scalable data solutions in a cloud-first environment. You will develop standardized reports and manage datasets that quantify financial and risk score impacts across Medicare Advantage and ACA programs.

You will collaborate with Informatics, Revenue Integrity, Actuarial, and Data Engineering teams to ensure data quality, model validation, and timely delivery of analytics outputs.

Qualifications

• 5+ years of experience in healthcare analytics, data management, data engineering, reporting, or business analytics.
• 3+ years of experience writing complex SQL queries in cloud-based environments such as BigQuery, Databricks, AWS, or similar platforms.
• Experience developing and supporting automated reporting, production processes, or data pipelines.

Responsibilities

• Develop, automate, and maintain monthly program evaluation and KPI reporting from multiple data sources.
• Maintain member-level risk adjustment datasets, risk score files, and outputs for Medicare Advantage and ACA programs.
• Migrate analytic processes from SAS to cloud-based solutions (BigQuery, Databricks, AWS, Python).
• Design and maintain cloud-based datasets, automated pipelines, and analytics infrastructure.

Skills

Healthcare analytics

SQL in cloud

Data engineering

Stakeholder communication

Git / version control

Education

Bachelor's degree in Analytics / Informatics / Statistics / CS

Tools

BigQuery

Databricks

AWS

Python

SAS

Job description

CVS Health seeks an experienced analytics professional to drive risk adjustment valuation initiatives and scalable data solutions in a cloud-first environment. You will develop standardized reports and manage datasets that quantify financial and risk score impacts across Medicare Advantage and ACA programs.

You will collaborate with Informatics, Revenue Integrity, Actuarial, and Data Engineering teams to ensure data quality, model validation, and timely delivery of analytics outputs.