Description :

Ensemble Health Partners AI Innovation group is the technical engine powering next-generation revenue cycle management solutions. Our team builds production-grade AI and ML systems that automate complex workflows, reduce operational friction, and deliver measurable outcomes for healthcare providers nationwide. We operate at the intersection of cutting-edge AI technology and real-world healthcare operations, with an uncompromising commitment to engineering excellence, Clean Architecture, and responsible AI.

Ensemble Health Partners is seeking an exceptional Lead, Analytics to join our AI Innovation group. This is a senior individual contributor and technical leadership role responsible for driving engineering excellence, executing systematic simplification initiatives, advancing agentic AI capabilities, and reducing technical debt across our revenue cycle AI platform. The ideal candidate combines deep technical craftsmanship with the ability to influence peers, mentor team members, and collaborate across organizational boundaries to deliver measurable business value.

Role & responsibilities :

Required Qualifications :

- Experience : 8+ years of total software engineering experience, including 5+ years in analytics, data science, or ML engineering roles, with at least 2 years in a technical lead or senior individual contributor capacity

Preferred Qualifications :

- Programming : Expert-level Python development with a strong emphasis on code quality, testability, and production-grade engineering

- MLEngineering : Demonstrated experience designing, training, deploying, and operating machine learning models in production

- CodeReview : Proven track record of driving engineering quality through rigorous, constructive code review at scale

- Pipeline Engineering : Hands-on experience building and maintaining ML pipelines, ETL processes, and data engineering workflows (Airflow, Azure Data Factory, or equivalent)

- Agentic AI : Working knowledge of agentic AI frameworks, LLM-based orchestration, and multi-agent system design

- Architecture : Familiarity with Clean Architecture principles, software design patterns, and system diagramming methodologies (C4 or equivalent)

- Collaboration : Demonstrated ability to work across organizational boundaries, influence without authority, and build alignment on technical decisions

Preferred Qualifications :

- Experience in healthcare revenue cycle management (RCM), including familiarity with claims processing, denials management, prior authorization, or related workflows

- Experience with cloud-based ML platforms (Azure ML, Azure Data Factory, Databricks, or equivalent)

- Experience with model simplification and generalization techniques including ensemble methods, transfer learning, and multi-task learning for reducing client-specific model proliferation

- Experience with LLM-based agentic frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar orchestration platforms

- Knowledge of AI governance and compliance frameworks such as NIST AI RMF, ISO 42001, or HITRUST