If you like the sweet spot where data science meets product reality (messy data, real users, real outcomes), this role is that. You’ll build ML and generative AI pipelines that help hospitals run cleaner, cheaper, and faster, especially on the revenue-cycle side.
About Ensemble Health Partners
Ensemble Health Partners provides technology-enabled revenue cycle management solutions for hospitals and affiliated physician groups, with a big push into AI-enabled automation and analytics.
Schedule
- Full-time
- Remote (Nationwide)
- Travel: may be required
- Experience target: 5–7 years overall (they also mention 3+ years as a data scientist)
- Education: Post-grad degree preferred (PhD/MSc) or equivalent experience
- Pay range: $83,200 – $159,450 (based on experience)
What You’ll Do
- Build and maintain AI/ML models and pipelines, focusing on generative AI, LLMs, and predictive modeling
- Lead AI strategy for complex, “clinical application” problems by combining stats + ML + practical engineering
- Run rigorous experiments and deliver measurable improvements
- Create reports/presentations that explain hypotheses, findings, and business impact clearly
- Own data discovery: collect, transform, explore, and become the “resident expert” on what data exists and how it behaves
- Collaborate across Product, Engineering, and Analytics to ship usable solutions into production
What You Need
- 3+ years working as a Data Scientist (they also list 5–7 years desired experience)
- Hands-on ML stack experience (3+ years): PyTorch/TensorFlow, scikit-learn, XGBoost (or equivalents)
- Strong programming (Python/R/SQL), statistical analysis, and data visualization skills
- Ability to design, test, deploy, and support ML models in production
- Experience with LLM pipelines, especially RAG and prompting (plus)
- Familiarity with LangChain/LlamaIndex/Haystack/Azure AI Studio, vector DBs, retrieval techniques (plus)
- Data engineering comfort: SQL + Azure Data Factory (or similar), or Hadoop/Spark
- Software engineering discipline: CI, unit/integration tests, code reviews
- MLOps fundamentals: orchestration, cloud compute, observability
- Able to work independently and cross-functionally, with strong communication
Benefits
- Bonus incentives
- Paid certifications
- Tuition reimbursement
- Comprehensive benefits
- Career advancement
Quick reality check (so you don’t waste time):
- They call it “Senior,” but the experience requirements are a little inconsistent (3+ years DS vs. 5–7 years total). That usually means they’ll flex title/pay based on who they get. If you’re closer to mid-level, you can still take a swing if your portfolio shows production impact.
- They mention “clinical applications,” but Ensemble is revenue cycle management. Translation: you’ll probably be working more on billing, collections, denials, and workflow automation than bedside medicine.
Happy Hunting,
~Two Chicks…