Clinical AI Analytics and Methods Consultant - MN preferred - Remote

UnitedHealth Group•Minnetonka, MN

3d•$112,700 - $193,200•Remote

About The Position

The Clinical AI Analytics & Methods Consultant serves as a senior analytics leader and methodological expert supporting the UHC Clinical AI Governance Council. This individual contributor role is responsible for ensuring that AI-enabled clinical use cases are evaluated with rigor, consistency, and clarity, and that analytic methods used in Council review are defensible, reproducible, and aligned to clinical risk, performance metrics, and defined success thresholds. The position owns the analytic framework and methods used to support AI vendor vetting and clinical AI review, ensuring that each use case is evaluated against clearly defined risk, metric, and threshold constructs to enable objective and consistent Council decision-making. The role also supports the design and execution of evaluations of clinical AI use cases as well as broader clinical programs, pilots, and interventions using real-world healthcare data. The role serves as the primary analytic and methodological liaison among Council leadership, program consultants, and subject matter experts across clinical, data science, and technical domains, translating complex analytic and AI concepts into clear, decision-ready materials for senior clinical leadership. The role has primary accountability for the methodological validity of Council-reviewed evidence.

Requirements

5+ years of experience designing and executing complex healthcare analytics or health services research initiatives
5+ years of experience working with real-world healthcare data (claims, EHR, or operational datasets)
5+ years of experience applying statistical methods and evaluation design in applied settings
5+ years of experience translating analytic outputs into decision-ready insights for leadership
3+ years of experience working across clinical, technical, and data science domains to align analytic inputs across stakeholders
Years of post-high school education can be substituted/is equivalent to years of experience

Nice To Haves

3+ years of experience evaluating predictive models, AI/ML applications (including NLP- and LLM-based systems), or algorithmic decision-support tools
Experience using analytic programming tools (e.g., SQL, Python, R, SAS) to design and execute analyses
Experience developing analytic datasets and conducting hands-on quantitative analyses using healthcare data
Advanced degree in quantitative field

Responsibilities

Partner with Council leadership and program consultants to apply the submission framework to each use case, ensuring analytic components align to defined risk, metric, and thresholds
Define measurable success criteria, translating clinical risks into metrics and thresholds for decision-making
Ensure complete and clearly defined evaluation methods at intake (data, population, comparators, metrics, and design)
Serve as the primary technical liaison across data science, clinical, and engineering SMEs, synthesizing inputs into a consistent evaluation approach
Ensure results support clear pass/fail decisions against defined thresholds
Develop concise, decision-ready summaries of performance vs thresholds, including key limitations
Serve as the methodological lead during Council review, addressing questions on evaluation design and results
Integrate analytic, clinical, and operational inputs into a single, aligned recommendation
Define analytic requirements for post-deployment monitoring, including metrics, thresholds, and triggers for re-review
Design and execute analytic evaluations of clinical AI use cases using real-world healthcare data
Perform hands-on data programming, analysis, and interpretation to support Council reviews and broader evaluation initiatives