Healthcare Data Scientist (Medicare/Medicaid)

Role overview Contribute to data science and machine learning work that helps identify potential fraud, waste, and abuse in public health insurance programs. Working with experienced analysts and engineers, you’ll explore claims data, develop analytical components, and communicate findings that support program integrity.

Responsibilities - Explore datasets and apply statistical methods and foundational supervised or unsupervised learning techniques. - Support predictive models, anomaly detection, and other analyses that flag potential improper activity. - Help build generative AI components such as prompt workflows, simple agents, embedding pipelines, or retrieval-based systems. - Prepare and maintain structured datasets using Python and SQL tools. - Create visualizations that explain data patterns and model results. - Document analyses and share findings with technical colleagues and project partners.

Requirements - Bachelor’s degree in a quantitative or technical field, or equivalent relevant background. - Around 1–3 years of experience in data science, analytics, or another quantitative discipline. - Experience using Python or R for analysis or machine learning, with familiarity with common data science libraries. - Knowledge of statistics and core machine learning concepts, including feature engineering, train/test splits, and evaluation metrics. - Familiarity with SQL and cloud or distributed data platforms. - Ability to interpret and communicate visualized data findings.

Nice to have - Experience with Medicare or Medicaid claims data, healthcare analytics, or program integrity. - Exposure to generative AI frameworks, embeddings, or vector databases. - Previous work with predictive modeling, anomaly detection, or fraud-related analytics.

Benefits and work setup - Remote role with a 40-hour work week and travel expected to be under 10%. - Benefits include medical, dental, and vision plans, a retirement plan with employer match, paid time off, holidays, and paid family leave.