Job description
Join a profitable healthcare AI company that deploys predictive models into the largest U.S. health systems and health plans. You will own 3 to 5 enterprise accounts end to end, from data integration and pilot design through production pipelines and ongoing operations.
What you'll do
- Design and defend commercially relevant experimental studies, such as predicting which patients need surgical intervention
- Build automated per-customer pipelines to train, score, and deliver insights at scale
- Run working sessions with client analytics, clinical, and IT teams
- Feed cross-account patterns back into the product roadmap
Compensation
$180,000 to $240,000 base, with on-target earnings of $200,000 to $260,000, plus competitive equity.
Location
Remote within the U.S., Eastern to Central hours preferred, with roughly quarterly travel. U.S. citizens and green card holders only.
Requirements
- 4+ years as an applied data scientist
- Healthcare or life sciences data experience (claims, EHR, HL7/FHIR, lab, population health)
- Has built a complex data or ML system end to end
- Client-facing experience owning accounts
- Experience designing and defending commercial experimental studies
- Distributed data and ML pipelines on Spark/PySpark
- Stack: Python, pandas, scikit-learn, Airflow, Spark, PySpark, AWS (S3, Glue, EMR, MWAA, SageMaker), SQL, Postgres
- U.S. work authorization (no sponsorship)