Industry/Sector
Health Services
Specialism
Data, Analytics & AI
Management Level
Senior Manager
Job Description & Summary
Growing as a strategic advisor, you leverage your influence, expertise, and network to deliver quality results. You motivate and coach others, coming together to solve complex problems. As you increase in autonomy, you apply sound judgment, recognising when to take action and when to escalate. You are expected to solve through complexity, ask thoughtful questions, and clearly communicate how things fit together. Your ability to develop and sustain high performing, diverse, and inclusive teams, and your commitment to excellence, contributes to the success of our Firm.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Craft and convey clear, impactful and engaging messages that tell a holistic story.
Apply systems thinking to identify underlying problems and/or opportunities.
Validate outcomes with clients, share alternative perspectives, and act on client feedback.
Direct the team through complexity, demonstrating composure through ambiguous, challenging and uncertain situations.
Deepen and evolve your expertise with a focus on staying relevant.
Initiate open and honest coaching conversations at all levels.
Make difficult decisions and take action to resolve issues hindering team effectiveness.
Model and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
The Opportunity
As part of the Applied AI Health System Engineering team, you will lead the development of AI, GenAI, and ML solutions tailored to the complex needs of health system and health plans. As a Senior Manager, you will drive use case development across clinical decision support, population health risk stratification, clinical research, and operational efficiency — translating ambiguous healthcare challenges into production-grade AI solutions. You will architect and build production-grade RAG pipelines, MCP connections, agentic AI workflows, and MLOps frameworks, managing daily operations across global delivery teams while engaging health system leaders at the executive level to ensure measurable clinical and operational impact.
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;
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