Senior Data Scientist – Value‑Based Car

 About Us:

Our purpose is to help clients exceed their financial health goals. Across the reimbursement cycle, our scalable solutions and clinical expertise help solve programmatic needs. Enabling our teams with leading technology allows analytics to guide our solutions and keeps us accountable achieving goals. 

We build long-term careers by investing in YOU. We seek to create an environment that cultivates your professional development and personal growth, as we believe your success is our success.  

JOB SUMMARY:

Domain: Healthcare Payer / Revenue Cycle Management | Programs: Medicare Advantage, ACA (Commercial Exchange), Medicaid | Platform: AWS | Role Type: Individual Contributor (hands‑on)

We are seeking a hands‑on Senior Data Scientist with strong medical coding and clinical domain expertise to support risk adjustment and quality initiatives for Value‑Based Care programs across Medicare Advantage, ACA health plans, and Medicaid.

This role focuses primarily on Risk Adjustment (HCC/RAF) and clinical indications, leveraging claims and clinical notes to deliver accurate, explainable, complete, and compliant analytics. The position is well‑suited for candidates with backgrounds in data science, biostatistics, bioinformatics, or clinical informatics, and experience applying traditional NLP and modern AI (LLMs, GenAI, agentic workflows) in regulated healthcare environments.

ESSENTIAL DUTIES AND RESPONSIBILITIES: 
Note: The essential duties and responsibilities below are intended to describe the general duties and responsibilities of this position and are not intended to be an exhaustive statement of duties. This position may perform all or most of the primary duties listed below. Specific tasks, responsibilities or competencies may be documented in the Team Member’s performance objectives as outlined by the Team Member’s immediate Leadership Team Member.

Location: Remote within US only

We are seeking a hands‑on Senior Data Scientist with strong medical coding and clinical domain expertise to support risk adjustment and quality initiatives for Value‑Based Care programs across Medicare Advantage, ACA health plans, and Medicaid.

This role focuses primarily on Risk Adjustment (HCC/RAF) and clinical indications, leveraging claims and clinical notes to deliver accurate, explainable, complete, and compliant analytics. The position is well‑suited for candidates with backgrounds in data science, biostatistics, bioinformatics, or clinical informatics, and experience applying traditional NLP and modern AI (LLMs, GenAI, agentic workflows) in regulated healthcare environments.

• Build and maintain risk‑adjustment analytic modeling (HCC suspecting, recapture models, RAF forecasting).
• Apply NLP and GenAI to medical records and clinical notes to extract structured clinical evidence.
• Develop LLM‑assisted and agentic workflows to support medical record coding review, evidence summarization, and improved productivity and accuracy.
• Perform forecasting and scenario analysis tied to operational capacity and financial impact.
• Monitor model performance, bias, drift, and documentation sufficiency.
• Ensure analytics are explainable, auditable, and compliant.
• Partner closely with Product, Engineering, Coding, Clinical, Compliance, and Operations teams.
• Translate analytics into actionable signals embedded in payer workflows.
• (Exposure to quality/HEDIS is a plus but not a primary focus.)
• (Exposure to/knowledge of physician workflows and patient condition capture/documentation is a plus.)

Required Skills & Experience

• Strong foundation in statistics, applied machine learning, and data analysis.
• Advanced Python and SQL.
• Experience working with medical records, claims and clinical data.
• Deep understanding of Risk Adjustment (CMS‑HCC, RAF mechanics).
• Deep understanding of medical coding (ICD‑10, CPT, DRG, NDC) and clinical documentation workflows.
• Experience delivering explainable models in regulated or audit‑sensitive environments.
• Clinical background and cross-referencing to medical record documentation requirements.
• Knowledge of CDI (Clinical Documentation Integrity) policies and procedures
• Strong communication and cross‑functional collaboration skills.

Technical & AI Stack

• Languages: Python and SQL are required, R is a plus.
• ML/DS model-building: pandas, numpy, scikit‑learn.
• NLP/GenAI: Large Language Models (LLMs), prompt engineering, retrieval‑augmented generation (RAG) pipelines, agentic AI for task orchestration and review; clinical NLP frameworks such as scispaCy and BioBERT.