Sr. Healthcare Data Scientist (Medicare/Medicaid)

• 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 Science, or a related field, or equivalent relevant experience.
• At least 5 years of professional experience in data science, including experience developing and applying advanced analytical models.
• At least 2 years of hands-on experience analyzing Medicare and/or Medicaid data, with a strong understanding of healthcare claims and program data.
• Proficiency in Python or R for data science and machine learning, with experience using tools such as Pandas, NumPy, TensorFlow, Scikit-learn, Seaborn, ggplot, or Matplotlib.
• Working knowledge of SQL and modern data platforms and technologies such as Databricks, Snowflake, and Spark.
• Hands-on experience with generative AI technologies and frameworks, such as LangChain, LangGraph, Hugging Face Transformers, vector databases, agent frameworks, or LLM orchestration tools.
• Strong understanding of statistics, machine learning fundamentals, predictive modeling, feature engineering, and model evaluation principles.
• Ability to lead analytical work independently while collaborating effectively across technical and business teams.
• Strong visualization, communication, and storytelling skills, with the ability to simplify complex data and AI concepts for varied audiences.
• A proactive, curious, self-directed mindset combined with strong problem-solving skills and a practical approach to applying emerging technologies.

Benefits

• Estimated annual salary range of $97,968–$132,250, with actual compensation determined by experience, geographic location, and applicable contractual requirements.
• Fully remote work environment with a standard 40-hour work week.
• Limited travel, generally less than 10%.
• Multiple medical plan options, including plans with Health Savings Accounts.
• Dental and vision insurance options.
• 401(k) retirement savings plan with company matching and pre- and post-tax contribution options.
• Flexible work arrangements where applicable to support work-life balance.
• Paid vacation, sick, personal, and holiday time, with typically 15 days of paid leave plus 10 paid holidays for new employees, subject to applicable policies and proration.
• Paid parental, military, bereavement, and jury-duty leave.
• Up to 160 hours of paid family leave during a rolling 12-month period for eligible employees.
• Short- and long-term disability coverage, life insurance, accidental death and dismemberment coverage, and additional accident and critical illness benefits.
• Opportunities to work with modern AI, cloud, data, and analytics technologies on impactful healthcare initiatives.