Growth-stage healthcare AI firm embedding predictive intelligence into enterprise clinical workflows.
Applied Data Scientist
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You are a pragmatic scientist who sees code as a clinical tool, not just an experiment, and you thrive when your models directly influence patient outcomes within major health systems. In this role, you will architect and deploy robust machine learning pipelines that move beyond proof-of-concept to become integral parts of daily operations for insurers and providers. Your work demands a rare blend of statistical rigor and engineering discipline to ensure AI agents perform reliably in high-stakes medical environments.
What they're looking for
- 4+ years of experience building production-grade ML systems using Python, Pandas, and Scikit-learn.
- Deep proficiency with big data frameworks like Spark or PySpark and orchestration tools such as Airflow.
- Proven track record of deploying models on AWS infrastructure with PostgreSQL backends.
- Strong understanding of healthcare data nuances, including claims, EHR, or wellness metrics.
- Ability to translate complex clinical problems into scalable data solutions without heavy supervision.