Analyze Medicare and Medicaid claims data using statistical methods and machine learning.
Develop generative AI-powered solutions and agent-based systems to detect fraud and streamline processes.
Build predictive models and anomaly detection to improve insights and program integrity.
Leverage CMS data with modern AI/ML methods, including LLMs, embeddings, vector databases, and retrieval-augmented pipelines.
Present findings to technical and non-technical stakeholders and leadership.

Key requirements

Analyze Medicare and Medicaid claims data using statistical methods and machine learning.
Develop generative AI-powered solutions and agent-based systems to detect fraud and streamline processes.
Build predictive models and anomaly detection to improve insights and program integrity.
Leverage CMS data with modern AI/ML methods, including LLMs, embeddings, vector databases, and retrieval-augmented pipelines.
Present findings to technical and non-technical stakeholders and leadership.

Jobs at GDIT

11 active roles from this employer in the JobMatcher catalog.

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Jobs at GDIT

11 active roles from this employer in the JobMatcher catalog.

All company jobs

About the role

Summary: GDIT is seeking a Senior Healthcare Data Scientist with deep experience in analytics for Medicare and Medicaid to help detect fraud, waste, and abuse using advanced analytics and AI. You will work with generative AI models, AI agents, and scalable data science tools to enhance fraud detection and optimize program integrity.

Responsibilities

Qualifications:

Analyze Medicare and Medicaid claims data using statistical methods and machine learning.
Develop generative AI-powered solutions and agent-based systems to detect fraud and streamline processes.
Build predictive models and anomaly detection to improve insights and program integrity.
Leverage CMS data with modern AI/ML methods, including LLMs, embeddings, vector databases, and retrieval-augmented pipelines.
Present findings to technical and non-technical stakeholders and leadership.
Perform additional duties as assigned.
Bachelor's degree in Statistics, Computer Engineering, Applied Mathematics or related field; 5+ years of data science experience; 2+ years of experience with Medicare/Medicaid data.
Proficiency in Python or R; experience with Pandas, NumPy, TensorFlow/Scikit-Learn, Seaborn/Matplotlib, GGPlot.
SQL, Databricks, Snowflake, Spark.
Hands-on experience with generative AI tools (LangChain, LangGraph, HuggingFace Transformers, vector databases, agent frameworks, or LLM orchestration).
Understanding of statistics and analytic model development (feature engineering, train/test split, etc.).
Ability to create data visualizations and communicate complex analyses clearly.
Self-sta

About the role

Summary: GDIT is seeking a Senior Healthcare Data Scientist with deep experience in analytics for Medicare and Medicaid to help detect fraud, waste, and abuse using advanced analytics and AI. You will work with generative AI models, AI agents, and scalable data science tools to enhance fraud detection and optimize program integrity.

Responsibilities

Qualifications:

Analyze Medicare and Medicaid claims data using statistical methods and machine learning.
Develop generative AI-powered solutions and agent-based systems to detect fraud and streamline processes.
Build predictive models and anomaly detection to improve insights and program integrity.
Leverage CMS data with modern AI/ML methods, including LLMs, embeddings, vector databases, and retrieval-augmented pipelines.
Present findings to technical and non-technical stakeholders and leadership.
Perform additional duties as assigned.
Bachelor's degree in Statistics, Computer Engineering, Applied Mathematics or related field; 5+ years of data science experience; 2+ years of experience with Medicare/Medicaid data.
Proficiency in Python or R; experience with Pandas, NumPy, TensorFlow/Scikit-Learn, Seaborn/Matplotlib, GGPlot.
SQL, Databricks, Snowflake, Spark.
Hands-on experience with generative AI tools (LangChain, LangGraph, HuggingFace Transformers, vector databases, agent frameworks, or LLM orchestration).
Understanding of statistics and analytic model development (feature engineering, train/test split, etc.).
Ability to create data visualizations and communicate complex analyses clearly.
Self-sta

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