Design, build, and maintain sophisticated predictive models using Python, SQL and AI Foundry
Apply machine learning techniques (e.g., gradient boosting, random forests, time-series modeling) to forecast outcomes and support proactive clinical interventions.
Validate, monitor, and refine predictive models for performance and reliability.
Conduct detailed analyses of utilization, cost patterns, quality outcomes, and value‑based care program performance.
Evaluate the impact of clinical programs, pilots, and interventions using rigorous statistical methods.
Deliver insights that improve total cost of care, reduce avoidable utilization, and enhance patient outcomes.
Develop and optimize analytical datasets using SQL and Python.
Build clean, user-friendly Power BI dashboards to communicate insights to market leadership, clinicians, and executives.
Ensure consistent data standards, documentation, and governance.
Use AI Foundry and other platforms to automate reporting, enhance data pipelines, and accelerate decision‑making.
Prototype AI-driven solutions that scale predictive intelligence across the organization.
Partner with clinical, operational, and finance teams to translate analytical findings into actionable strategies.
Identify gaps, risks, and opportunities—then help design data‑driven solutions to improve outcomes and operational performance.
Present insights in a clear, compelling manner tailored to diverse audiences.

Bachelor’s degree in Healthcare Economics, Data Science, Public Health, Statistics, or related field.
4+ years of analytics experience in healthcare, healthcare economics, or value‑based care.
Strong proficiency in SQL (2+ years of SQL experience) and Python
Experience working with healthcare claims, EHR data, or Medicare/MA/ACO datasets.
Experience developing predictive models or machine learning applications.
Excellent communication skills, including the ability to translate complex analytics into actionable insights.

Senior Analyst, Healthcare Economics

Key skills