Principal Data Analyst and AI Liaison - Remote in EST, CST, or MST

UnitedHealth Group•Minnetonka, MN

1d•$112,700 - $193,200•Remote

About The Position

The Principal Data Analyst & AI Liaison plays a critical role at the intersection of healthcare operations, big data analytics, and applied artificial intelligence. This role is responsible for translating large, complex healthcare datasets into actionable insights while serving as a bridge between clinical, operational, technical, and AI development teams. The role ensures that AI tools and advanced analytics are implemented responsibly, effectively, and in alignment with clinical, regulatory, and business needs. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

5+ years of experience in healthcare data analysis, analytics, or health tech roles
5+ years of SQL programming experience
3+ years of SAS programming experience
Demonstrated expertise working with large scale claims and healthcare datasets
Solid understanding of health plan economics and performance levers

Nice To Haves

Advanced experience querying and integrating large disparate data sources using SAS
Experience supporting or implementing AI/ML solutions in healthcare
Translational mindset - able to turn data and AI into real world outcomes
Experience with population health, value based care, or clinical quality analytics
Familiarity with healthcare regulations (HIPAA, AI governance, data privacy)
Ability to balance innovation with clinical risk and regulatory constraints
Ability to collaborate across clinical, technical, and business teams
Solid analytical thinking and problem solving abilities
Excellent communication and stakeholder management skills

Responsibilities

Analyze large-scale healthcare datasets (clinical, claims, operational, financial, population health) to identify trends, inefficiencies, and improvement opportunities
Develop dashboards, reports, and data models that support clinical quality, patient outcomes, cost optimization, and operational efficiency
Ensure data accuracy, integrity, normalization, and governance across systems
Partner with clinical and operational leaders to translate business questions into analytical approaches
Serve as the primary liaison between business/clinical stakeholders and AI/ML teams or vendors
Evaluate, pilot, and support deployment of AI tools (e.g., predictive analytics, NLP, computer vision, automation, large language models)
Translate healthcare workflows and requirements into AI ready use cases
Validate AI outputs for clinical relevance, bias, explainability, and regulatory compliance
Support responsible AI practices, including documentation, monitoring, and human in the loop controls
Work x-functionally and produce analytics and reports and draw business and clinical insights to identify target patient and provider population, and moment of influence
Define outcome and success metrics and set targets with clinical program leaders
Ongoing monitoring of clinical programs and pilots and refine targets
Retrospective formal program evaluation using advanced econometrics
Create reports and data visualizations to share insights with stakeholders
Maintain documentation of methodology of opportunity analysis/impact evaluation analysis so they are ready to quickly scale to multiple programs and interventions across types of services, care paths/diagnosis groups and lines of business (e.g., Medicare Advantage, commercial Medicaid)
Support use of EHR, claims, device, and third party data sources and sources of data
Communicate complex data and AI concepts in clear, non technical language
Educate leaders and end users on AI capabilities, limitations, and best practices
Support training and adoption of AI enabled tools within clinical and operational teams