Sr. Value-Based Healthcare Data Analyst - Kelsey-Seybold, Pearland, TX

UnitedHealth Group•Pearland, TX

9d•$91,700 - $163,700•Onsite

About The Position

The Senior Value-Based Healthcare Data Analyst is responsible for providing leadership and advanced analytical expertise to support healthcare quality, regulatory, and operational reporting initiatives, including HEDIS, EDPS, and encounter submissions. This position ensures accuracy, integrity, traceability, and compliance of complex, multi-source healthcare data in accordance with NCQA, CMS, and state regulatory requirements. The role functions as a hands-on technical leader, supervising analytic activities and coordinating efforts across Quality, Clinical, Informatics, IT, and Business Intelligence teams. Through collaboration and data-driven insights, the position supports organizational objectives related to quality performance, affordability, and improved member outcomes. You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Requirements

Bachelor’s degree in health informatics, Healthcare Administration, Data Analytics, Statistics, Computer Science, Information Systems, Mathematics, or related discipline
3+ years of experience in healthcare data analytics, informatics, decision support, or managed care, including project leadership or analyst mentoring
Hands-on experience supporting Medicare Advantage (Part C) and/or Health Insurance Marketplace products
Experience supporting NCQA HEDIS Compliance Audits, quality measurement, and value-based care programs
Demonstrated experience extracting, reconciling, and validating data from EPIC Clarity and/or Caboodle
Solid experience with data validation, ETL processes, and healthcare reporting tools (e.g., Tableau, Power BI, Crystal Reports)
Deep knowledge of Medicare Advantage, including Stars, HEDIS, and regulatory reporting programs
Thorough understanding of HEDIS Technical Specifications, NCQA requirements, and related compliance standards
Advanced proficiency in SQL and Microsoft Excel, with working knowledge of Word and PowerPoint
Solid proficiency working with claims and clinical data, including ICD-10-CM and CPT/HCPCS coding standards and healthcare data models

Nice To Haves

Master’s degree in health informatics, Data Science, Analytics, Biostatistics, Healthcare Administration, or a related field
Certified Professional in Healthcare Quality (CPHQ)
Registered Health Information Administrator (RHIA) or (RHIT)
Epic certification (Clarity, Caboodle, or reporting modules)
Certified Analytics Professional (CAP)
SAS, SQL, or data analytics-related certifications
3+ years of experience with EDI encounter data (837), acknowledgments (277CA/999), and CMS risk adjustment files (MAO-002, MAO-004, RAPS)
Experience reviewing others’ work and providing constructive recommendations for improvement
Advanced familiarity with EPIC Clarity architecture, refresh cycles, and enterprise data warehouse integration supporting BI and reporting environments
Solid background in healthcare analytics, quality metrics, and advanced value-based care models
Proficiency with Python, R, SAS, or similar statistical or programming languages
Demonstrated ability to balance strategic perspective with hands-on technical execution

Responsibilities

Providing leadership and advanced analytical expertise to support healthcare quality, regulatory, and operational reporting initiatives, including HEDIS, EDPS, and encounter submissions.
Ensuring accuracy, integrity, traceability, and compliance of complex, multi-source healthcare data in accordance with NCQA, CMS, and state regulatory requirements.
Functioning as a hands-on technical leader, supervising analytic activities and coordinating efforts across Quality, Clinical, Informatics, IT, and Business Intelligence teams.
Supporting organizational objectives related to quality performance, affordability, and improved member outcomes through collaboration and data-driven insights.
Proactively identify and communicate risks, delays, data issues, and recommended solutions to stakeholders.
Independently monitor data pipelines, submissions, and measure results for anomalies, gaps, or logic errors.