Partner with clinical and utilization management teams to understand workflows, data needs, and areas where analysis can improve decision-making and outcomes
Use AI tools to accelerate data pulls and surface patterns across large clinical datasets
Analyze AI findings to flag trends or anomalies that may not be immediately visible through manual review
Leverage AI to support documentation tasks such as drafting summaries, structuring findings, and generating repeatable templates for clinical and operational use
Pull, clean, and analyze healthcare data including claims, date of service, provider specialty, utilization patterns, and clinical indicators
Identify trends and draw actionable insights from clinical and utilization data to support care management, cost containment, and quality improvement efforts
Support the clinical team in understanding benefit structures, plan designs, and how they interact with utilization and outcomes data
Identify opportunities where AI or automation could streamline clinical review processes, flag outliers, or reduce manual workload for clinical staff
Build lightweight data tools, dashboards, or summary reports to make clinical and utilization data more accessible and actionable
Document findings, methodologies, and recommendations clearly so insights are repeatable and usable beyond the internship
Present data findings and recommendations to clinical and operational leadership in a clear, accessible format

Currently a Senior or Graduate student enrolled in a degree program in Health Informatics, Nursing, Clinical Health Sciences, Public Health, Healthcare Administration, or a related field
Clinical or medical knowledge sufficient to understand healthcare terminology, diagnosis and procedure codes, provider specialties, and utilization management concepts
Experience working with or analyzing healthcare data, including claims data, date of service, provider information, or clinical documentation
Strong analytical skills with the ability to draw meaningful insights from complex datasets
Hands-on familiarity with AI tools (such as ChatGPT, Claude, Copilot, or similar) and demonstrated ability to apply them practically
Curiosity about how AI can improve healthcare operations – you don’t need to be an AI engineer, but you should be someone who experiments, asks “what if we used AI for this?” and follows through
Familiarity with data tools such as Excel, SQL, Tableau, Power BI, or similar platforms
Ability to communicate data findings clearly to both clinical and non-clinical audiences
Ability to work independently, manage ambiguity, and prioritize across multiple projects
Experience with Python, R, or other data analysis languages is a plus
Prior exposure to utilization management, care management, or managed care environments is a plus

Healthcare Informatics AI Intern

Key skills