Leads client-facing healthcare AI and data science engagements, managing teams that design, develop, validate, and deploy HIPAA-compliant AI and GenAI solutions. Responsibilities include architecture, healthcare process analysis, model and LLM selection, RAG and agentic workflow development, data engineering, MLOps, stakeholder presentations, team coaching, and delivery oversight across clinical, financial, and operational health system use cases.
The Opportunity
As an Applied AI Health Services Data Science-Senior Manager you will lead client-facing work focused on designing and developing AI-enabled data solutions that transform raw information into usable insights and support intelligent decision-making. As a Senior Manager you will lead large projects, shape delivery approaches, and bring sound judgment, influence, and coaching skills to guide teams through complex work within our Advisory practice. In this role at PwC, you will draw on data and analytics engineering, artificial intelligence, and machine learning skills to develop models, systems, and workflows that support automation, improve business processes, and translate business needs into practical technical solutions.
You will work across multidisciplinary teams, communicate clearly with clients and internal stakeholders, and bring structure to changing priorities while driving operational excellence. The role calls for a strategic mindset, the ability to recognize when to act or escalate, and a focus on developing inclusive teams that can move work forward with composure and accountability.
Responsibilities
- 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;
- Guiding system architecture choices across cloud platforms, model integration patterns, and data pipelines to support scalable AI deployment
- Validating model outputs, evaluation methods, and feedback loops using complex data analysis, AI fluency, and data modeling techniques
- Coaching teams through ambiguous delivery challenges, while directing issue resolution and escalating risks when needed
- Crafting clear status updates, solution narratives, and implementation recommendations for client stakeholders and internal leaders
- 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,
- Identifying improvement opportunities in AI implementation, operational workflows, and platform usage across data, analytics, and automation programs
What You Must Have
- At least a 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
What Sets You Apart
- Preference for at least one of the following fields of study: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating applied AI system design across health services environments
- Applying systems thinking to data pipelines, models, and platform integrations
- Translating complex findings into clear, client-facing guidance
- Coaching teams through ambiguity, change, and delivery challenges
- Vectorization and embedding of clinical text, prompt engineering for healthcare contexts, RAG (retrieval-augmented generation) workflow development for clinical knowledge retrieval, and design of agentic AI workflows for multi-step healthcare processes such as prior authorization, care gap identification, and revenue cycle task automation;
- Hands-on experience with Azure (including Azure OpenAI Service, Azure Machine Learning, and Azure Health Data Services), AWS (SageMaker, Bedrock), and/or Google Cloud (Vertex AI) platforms, with an understanding of PHI-compliant deployment patterns and HIPAA-aligned cloud configurations;
- Experience with data warehouse technology including Snowflake or Databricks
- Experience working with Anthropic - Claude and Claude code to accelerate development and build applications
- Experience with Git version control, unit/integration/end-to-end testing, CI/CD, and MLOps practices including model monitoring, performance drift detection, and model governance frameworks appropriate for regulated healthcare environments.
- Using cloud engineering skills with AWS, Azure, or Google Cloud
The salary range for this position is: $124,000 - $280,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance
As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.
PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.
Learn more about how we work: https://pwc.to/how-we-work
For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.
Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines
#LI-Hybrid
#BI-Hybrid
As an Applied AI Health Services Data Science-Senior Manager you will lead client-facing work focused on designing and developing AI-enabled data solutions that transform raw information into usable insights and support intelligent decision-making. As a Senior Manager you will lead large projects, shape delivery approaches, and bring sound judgment, influence, and coaching skills to guide teams through complex work within our Advisory practice. In this role at PwC, you will draw on data and analytics engineering, artificial intelligence, and machine learning skills to develop models, systems, and workflows that support automation, improve business processes, and translate business needs into practical technical solutions.
You will work across multidisciplinary teams, communicate clearly with clients and internal stakeholders, and bring structure to changing priorities while driving operational excellence. The role calls for a strategic mindset, the ability to recognize when to act or escalate, and a focus on developing inclusive teams that can move work forward with composure and accountability.
Responsibilities
- 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;
- Guiding system architecture choices across cloud platforms, model integration patterns, and data pipelines to support scalable AI deployment
- Validating model outputs, evaluation methods, and feedback loops using complex data analysis, AI fluency, and data modeling techniques
- Coaching teams through ambiguous delivery challenges, while directing issue resolution and escalating risks when needed
- Crafting clear status updates, solution narratives, and implementation recommendations for client stakeholders and internal leaders
- 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,
- Identifying improvement opportunities in AI implementation, operational workflows, and platform usage across data, analytics, and automation programs
What You Must Have
- At least a 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
What Sets You Apart
- Preference for at least one of the following fields of study: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating applied AI system design across health services environments
- Applying systems thinking to data pipelines, models, and platform integrations
- Translating complex findings into clear, client-facing guidance
- Coaching teams through ambiguity, change, and delivery challenges
- Vectorization and embedding of clinical text, prompt engineering for healthcare contexts, RAG (retrieval-augmented generation) workflow development for clinical knowledge retrieval, and design of agentic AI workflows for multi-step healthcare processes such as prior authorization, care gap identification, and revenue cycle task automation;
- Hands-on experience with Azure (including Azure OpenAI Service, Azure Machine Learning, and Azure Health Data Services), AWS (SageMaker, Bedrock), and/or Google Cloud (Vertex AI) platforms, with an understanding of PHI-compliant deployment patterns and HIPAA-aligned cloud configurations;
- Experience with data warehouse technology including Snowflake or Databricks
- Experience working with Anthropic - Claude and Claude code to accelerate development and build applications
- Experience with Git version control, unit/integration/end-to-end testing, CI/CD, and MLOps practices including model monitoring, performance drift detection, and model governance frameworks appropriate for regulated healthcare environments.
- Using cloud engineering skills with AWS, Azure, or Google Cloud
The salary range for this position is: $124,000 - $280,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance
As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.
PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.
Learn more about how we work: https://pwc.to/how-we-work
For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.
Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines
#LI-Hybrid
#BI-Hybrid
PwC Denver, Colorado, USA Office
1900 Sixteenth Street, Denver, CO, United States, 80202
Similar Jobs at PwC
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Provides administrative and concierge support to senior leaders by managing calendars, meetings, travel, confidential information, correspondence, records, expenses, and action items. Coordinates office logistics, guest services, conference rooms, virtual sessions, and special events while maintaining organized workflows and adapting to changing priorities.
Top Skills:
Data Entry And Reporting ToolsOffice Productivity ToolsTravel Systems
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Supports external financial statement audits for Japanese business clients by reviewing financial records, testing balances and internal controls, analyzing account activity, documenting findings, preparing workpapers, and assisting with walkthroughs and substantive procedures. The role applies GAAP, GAAS, accounting methodologies, and data analysis tools while collaborating with audit teams and communicating with clients. It is designed for entry-level candidates developing audit, financial reporting, and technical accounting skills.
Top Skills:
Data AnalysisData ModelingGaapGaasInternal Controls
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Leads client-facing SAP finance workstreams from planning through delivery. Analyzes finance processes, designs SAP FI, FICO, and Central Finance solutions, supports configuration and testing, and improves reporting and transaction processing. Manages project scope, budgets, timelines, risks, and issue resolution while coaching junior consultants, reviewing deliverables, coordinating stakeholders, and supporting deployment and post-go-live activities.
Top Skills:
Sap Central FinanceSap Core ErpSap FiSap FicoSap Reporting And Analytics
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
