Sr. Data Scientist - Value Based Care Domain

Virtix Health (a CorroHealth Company)
partners with health plans across the country to drive clinical, financial, and operational results. Virtix Health offers virtual wellness visits, in-home health risk assessments, retrospective chart review, workflow technology and member/patient engagement service offerings for health plans of all sizes.

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.

Key Responsibilities

• 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.
• Data & Compute: AWS (RDS for SQL Server, S3, Redshift, Snowflake, Athena), Azure (Foundry, OpenAI Service, Machine Learning).
• Analytics: Jupyter, Power BI.
• MLOps: experiment tracking and model/version management (e.g., MLflow).

Preferred Background

• Experience supporting Medicare Advantage risk adjustment programs.
• Experience with ACA health plan populations and Medicaid.
• Background in bioinformatics, biostatistics, public health, biomedical informatics, or clinical data science.
• Experience with medical record coding and CDI.
• Familiarity with FHIR data and healthcare interoperability standards.
• Prior work in payer RCM or value‑based care analytics.
• Experience supporting compliance‑reviewed or audit‑exposed models.
• Practical experience deploying or piloting LLM‑ or GenAI‑based solutions.