Data Scientist - Healthcare Fraud Waste and Abuse - REMOTE - 256553

Role Overview

Data Scientist – Healthcare Fraud, Waste and Abuse (FWA) (Fully Remote)

• Type: Contract to Hire (converts to full-time within ~6 months)
• Level: Associate (requires 3–5 years experience)
• Location: United States (must live in the US; EST/CST hours)

Responsibilities

• Build and deploy predictive models to detect anomalies and patterns associated with healthcare claims fraud, waste, and abuse.
• Develop and own data products to automatically identify and prevent FWA.
• Create and optimize data pipelines for structured and unstructured sources (text, documents, images) with LLM/multimodal use cases.
• Design, develop, and deploy LLM-based solutions, including RAG, embeddings, and instruction tuning for claims handling and document understanding.
• Perform deep-dive analyses with heavy SQL and predictive modeling to surface actionable patterns.
• Use agentic AI tools to integrate and maintain advanced operational workflows that connect vendor solutions with client environments.
• Collaborate with leadership and business teams to embed automated data processes into revenue cycle workflows.
• Visualize results via dashboards and present findings to non-technical stakeholders and/or legal teams.

Required Skills

• B.S. degree.
• 2+ years of healthcare domain experience focused on Revenue & Finance and Fraud/Waste/Abuse.
• Strong applied statistics, including regression and clustering.
• Advanced hands-on Python (with PySpark, NumPy, SciPy).
• Advanced hands-on SQL.
• No C2C; must be permanently authorized to work in the US (no visa sponsorship).

Nice-to-Haves

• Experience building LLM solutions for document understanding and claims handling (RAG/embeddings/instruction tuning).