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About the role
Serve as a trusted advisor to C-suite and clinical executive leadership on quality strategy, investment prioritization, and reputational risk tied to public rankings. Ability to work independently as a senior IC operating with director-level scope, autonomy, and executive exposure — driving projects end-to-end from clinical hypothesis to deployed algorithm to executive-level recommendation.
What they're looking for
- Clinical background and licensure/credentialing (e.g., RN, MD/DO, PharmD, or equivalent clinical degree) or a graduate degree in Clinical/Health Informatics with substantial hands-on clinical quality experience
- 10+ years of experience in clinical informatics, clinical quality, CDI, or population health analytics, including direct experience with hospital ranking/rating methodologies
- 5+ years of hands-on experience building data pipelines and/or ML models in Databricks (Spark, Delta Lake, MLflow), strong SQL and Python skills
- Demonstrated experience applying AI/ML (including NLP/LLM techniques) to clinical and/or claims data for gap detection, risk stratification, or quality measurement
- Deep working knowledge of ICD-10-CM/PCS coding, risk-adjustment models (e.g., APR-DRG, MS-DRG, HCC/RAF), and how coding/documentation quality affects publicly reported outcomes
- Ability to work independently as a senior IC operating with director-level scope, autonomy, and executive exposure — driving projects end-to-end from clinical hypothesis to deployed algorithm to executive-level recommendation
More about this role
We are seeking a senior individual contributor — a role with director-level strategic scope and executive visibility who sits at the intersection of clinical medicine, health care quality benchmarking, and applied data science/AI. This person will combine deep clinical informatics expertise with hands-on Databricks engineering and AI/ML skill to build algorithms that do two things simultaneously: (1) close documentation and coding gaps that affect risk adjustment, mortality index, and quality attribution, and (2) identify gaps and variation in the actual clinical processes of care that drive the metrics used by national hospital ranking and rating programs (e.g., CMS Star Ratings, U.S. News & World Report, Leapfrog, Vizient, Healthgrades, IBM Watson Health/Chartis 100 Top Hospitals).
This is not a traditional CDI (clinical documentation integrity) role, and it is not a traditional data engineering role — it is a hybrid role for someone who can translate clinical nuance into data science problems, build and productionize those solutions in Databricks, and connect the output directly to performance improvement and public reputation/ranking outcomes.
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