Responsibilities - Oversee the development of healthcare AI and GenAI solutions, including clinical use case design, analytical modeling, prompt engineering, and RAG pipeline development - Lead large healthcare data science engagements, innovating delivery processes and driving continuous improvement across use case development lifecycles - Maintain operational excellence while engaging health system clinical, financial, and operational leaders at a senior level to align AI initiatives with organizational priorities - Guide teams in processing clinical notes, claims data, ADT feeds, and other structured and unstructured healthcare data sources for use in AI and LLM-powered solutions - Manage daily operations of a global healthcare data science team, overseeing model development, MLOps practices, and model governance across client engagements - Contribute to the creation of healthcare AI proof of concepts, pilots, and production use cases spanning clinical decision support, revenue cycle, population health, research (including images and genomics) and operational optimization - Foster a collaborative environment across clinical, technical, and operational team members to solve complex health system data science challenges - Maintain excellence in client service and satisfaction, helping health system clients realize tangible value from AI and ML investments What You Must Have - Bachelor's Degree - 12 years of experience, with meaningful exposure to healthcare data science, health IT, or AI solution development for health system clients - At least 6-7 years of experience at a health system Preferred Knowledge/Skills Demonstrates in-depth level abilities and/or a proven record of success managing the identification and addressing of health system needs Domain expertise in the healthcare value chain including but not limited to Claims, Pharmacy, Finance, Clinical Domains Managing development teams in building healthcare AI and GenAI solutions, including analytical modeling, prompt engineering, Python-based development, testing, communication of results to clinical and operational stakeholders, front-end and back-end integration, and iterative use case development with health system clients; Documenting and analyzing healthcare business processes - across clinical operations, and population health programs - to identify AI and GenAI opportunities, gather requirements, define initial hypotheses, and develop solution approaches tailored to health system workflows; Collaborating with health system client teams - including clinical informatics, population health, and IT leaders - to understand their business and clinical problems and select the appropriate models, LLMs, and approaches for AI/GenAI use cases; Designing and solutioning AI/GenAI architectures for health system clients, including RAG-based clinical knowledge retrieval systems, agentic AI workflows for care management and revenue cycle automation, and custom LLM application builds with appropriate PHI safeguards; Managing teams to process healthcare unstructured and structured data - including clinical notes, discharge summaries, claims records, EHR data, and ADT feeds - for use as LLM context, including embedding of large clinical text corpora, generative SQL query development, and building connectors to EHR back-end databases; Managing daily operations of a global healthcare data science team on client engagements, reviewing developed models, providing feedback, and assisting in analysis of clinical and operational outcomes; Directing data engineers and other data scientists to deliver efficient, HIPAA-compliant solutions that meet health system client requirements for clinical, financial, and operational AI use cases; Leading and contributing to development of proof of concepts, pilots, and production use cases for health system clients - spanning clinical decision support, prior authorization automation, patient risk scoring, workforce optimization, and throughput modeling - while working in cross-functional teams; Facilitating and conducting executive-level presentations to health system leadership showcasing GenAI and ML solution capabilities, use case development progress, model performance, and recommended next steps; Structuring, writing, communicating, and facilitating client presentations that translate complex AI and ML concepts into clear clinical and business value narratives for health system audiences; and, Managing associates and senior associates through coaching, providing feedback, and guiding work performance, with an emphasis on developing healthcare domain knowledge alongside technical AI and ML capabilities. What Sets You Apart - Demonstrated experience delivering production AI or GenAI use cases in a health system environment, with measurable clinical or financial outcomes - Hands-on experience building RAG pipelines or agentic AI workflows against clinical data sources, including EMR - Experience with MLOps platforms and model governance practices in regulated, PHI-handling environments - Ability to translate clinical and revenue cycle workflows into structured AI use case requirements and scalable solution designs - Familiarity with Azure OpenAI Service, AWS Bedrock, or Google Vertex AI in a HIPAA-compliant deployment context - Understanding of value-based care, population health program design, or clinical quality measurement and how AI accelerates outcomes in these areas The salary range for this position is: $124,000 - $280,000.