Sr. Healthcare Data Scientist (Medicare/Medicaid)

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Sr. Healthcare Data Scientist (Medicare/Medicaid) based in the Netherlands.
This role offers the opportunity to apply advanced data science and AI to some of the most complex challenges in healthcare program integrity.
You will analyze large-scale Medicare and Medicaid claims data to uncover patterns associated with fraud, waste, and abuse.
The position combines statistical modeling, machine learning, generative AI, and agent-based technologies to create innovative analytical solutions.
You will work with modern tools including LLMs, embeddings, vector databases, and retrieval-augmented pipelines.
Your insights will support better decision-making, operational efficiency, and stronger outcomes across healthcare programs.
The environment is collaborative and mission-driven, with opportunities to translate sophisticated technical work into clear recommendations for diverse audiences.
This is an ideal opportunity for a curious, hands-on data scientist who wants to make meaningful impact through healthcare analytics and emerging AI technologies.

Accountabilities

Analyze Medicare and Medicaid claims data using statistical methods, machine learning, and advanced analytical techniques to identify trends, anomalies, and potential fraud, waste, and abuse.
Develop generative AI-powered solutions and agent-based systems to strengthen fraud detection, investigate complex patterns, and improve business processes.
Build predictive, anomaly detection, and other analytical models that improve program integrity, operational efficiency, and actionable insights.
Identify opportunities to apply large-scale CMS data with modern AI and machine learning approaches, including LLMs, embeddings, vector databases, and retrieval-augmented generation pipelines.
Apply sound data science practices including feature engineering, attribute selection, threshold setting, model validation, and train/test methodologies.
Create clear and effective data visualizations that communicate complex findings and emerging trends.
Present analytical results and recommendations to both technical and non-technical stakeholders, including senior leadership.
Contribute to additional analytical, data science, and AI initiatives as required.

Requirements

Bachelor’s degree in an analytical or technical discipline such as Statistics, Computer Engineering, Applied Mathematics, Data...