Vice President Data and Artificial Intelligence

Overview

At SCA Health, we believe healthcare is about people – the patients we serve, the physicians we support and the teammates who push us forward. Behind every successful facility, procedure or innovation is a team of 15,000+ professionals working together, learning from each other and living out the mission, vision and values that define our organization.

As part of Optum, SCA Health is redefining specialty care by developing more accessible, patient-centered practice solutions for a network of more than 370 ambulatory surgical centers, over 400 specialty physician practice clinics and numerous labs and surgical hospitals. Our work spans a broad spectrum of services, all designed to support physicians, health systems and employers in delivering efficient, value-based care to patients without compromising quality or autonomy.

What sets SCA Health apart isn’t just what we do, it’s how we do it . Each decision we make is rooted in seven core values :

Clinical quality

Integrity

Service excellence

Teamwork

Accountability

Continuous improvement

Inclusion

Our values aren’t empty words – they inform our attitudes, actions and culture. At SCA Health, your work directly impacts patients, physicians and communities. Here, you’ll find opportunities to build your career alongside a team that values your expertise, invests in your success, and shares a common mission to care for patients, serve physicians and improve health care in America.

At SCA Health, we offer a comprehensive benefits package to support your health, well-being, and financial future. Our offerings include medical, dental, and vision coverage, 401k plan with company match, paid time off, life and disability insurance, and more. Click here to learn more about our benefits.

Your ideas should inspire change. If you join our team, they will .

Responsibilities

SCA Health is building the data and AI foundation that will define its competitive position as the leading ambulatory surgery company in the United States. This is a greenfield executive leadership role — a chance to shape strategy, build a team, and establish the governance and technology platforms that will serve SCA's 300+ facilities and 12,000+ associates for the next decade. The VP, Data & AI reports directly to the CIO and is one of eight direct reports on the CIO's leadership team. You will own the enterprise data strategy, platform, and governance function, and will lead SCA's AI and machine learning capability — from foundational MLOps infrastructure through clinical decision support and operational AI at scale. This role sits at the intersection of healthcare's two most consequential technology shifts: the transition to data-driven clinical and operational decision-making, and the responsible deployment of AI in care delivery. You will work in direct partnership with SCA's CMO, CFO, COO, CGO, and clinical leaders — not just the technology organization.

Core Accountabilities:

Enterprise Data Strategy & Platform. Define and execute SCA Health's multi-year data platform roadmap — cloud data architecture, EHR/PAS data integration (HST, Athena, eCW, etc.), real-time pipelines, and the infrastructure that makes trusted data available to every decision-maker across the enterprise.

AI & Machine Learning Strategy. Lead SCA's AI roadmap — from MLOps infrastructure and model development through production deployment and monitoring. Prioritize use cases with rigorous business case analysis and establish clinical validation protocols.

Responsible AI & Ethics Framework. Establish SCA's responsible AI standards — model documentation, bias monitoring, explainability requirements, and the AI Review Board that ensures every clinical AI deployment meets the highest standards of safety and transparency. Track FDA SaMD guidance.

Cross-Functional Enterprise Partnership. Operate as the data and AI thought leader for the enterprise — partnering with VP Product on data-informed product decisions, with CISO on data security and AI risk, with Head of Architecture on platform design, and with clinical and operational leaders on use case identification and adoption.

Team Building & Talent Development. Build and lead a high-performing team of 12–15 data and AI professionals across six functional areas. Establish a culture of rigor, curiosity, and clinical partnership that attracts top talent in a competitive market.

Investment & Vendor Management. Own the Data & AI technology budget, vendor evaluation, and contract strategy. Make disciplined build/buy/partner decisions and defend investment priorities with rigorous ROI analysis to executive and board-level audiences.

Shared Accountabilities:

Data Governance & Quality. Support evolving SCA’s enterprise data governance framework — ownership model, data dictionary, quality standards, master data management, and compliance posture across HIPAA, TEFCA/HTI-1, and emerging interoperability mandates. Function currently reports to Sr. VP of Innovation.

What the role does not own:

Analytics & BI: Remains with the Payer Analytics team, not IT. VP Data & AI is an enabler of analytics capability — providing clean data, governed pipelines, and platform access — but does not own the Analytics & BI roadmap or outcomes.

Qualifications

Required Experience:

10+ years in data, analytics, or AI leadership roles, with 4+ years at VP or equivalent level

Demonstrated experience building enterprise data platforms at scale (cloud-native, modern data stack: dbt, Spark, Databricks or Snowflake)

Healthcare data experience required — EHR integration (HL7/FHIR), HIPAA compliance, clinical data structures and terminology

Hands-on experience leading AI/ML initiatives from business case through production deployment and ongoing monitoring

Proven track record building and leading high-performing technical teams of 10+ people in complex organizations

Experience establishing data governance frameworks in multi-site or distributed healthcare organizations

Preferred Experience:

Ambulatory surgery, surgical specialty, or multi-site healthcare network experience

Familiarity with FDA Software as a Medical Device (SaMD) regulatory framework for clinical AI

Experience deploying generative AI in enterprise or clinical settings (RAG pipelines, LLM evaluation, guardrails)

Track record of data product thinking — not just infrastructure, but data as a product consumed by business users

Graduate degree in computer science, data science, statistics, biomedical informatics, or related field

Experience operating in a PE-backed or high-growth acquisition-driven environment

Technical Depth Expected:

Cloud data platforms: Databricks, Snowflake, or Azure Synapse — architectural fluency required (not just familiarity)

Healthcare interoperability: HL7 v2, FHIR R4, SMART on FHIR — integration pattern experience

ML frameworks and MLOps: MLflow, Kubeflow, SageMaker, or Vertex AI

Data governance tooling: Collibra, Alation, or equivalent enterprise catalog platforms

BI and analytics: Tableau, Power BI, or Looker — platform strategy and semantic modeling

GenAI patterns: RAG architecture, LLM evaluation frameworks, prompt engineering at enterprise scale

Leadership Profile:

Equally fluent in the executive boardroom and the data architecture whiteboard — not one or the other

Build trust with clinicians and operational leaders; demonstrates clinical context, not just technical empathy

Makes decisions with data, not just instinct — models the culture they are trying to build

Comfortable with greenfield environments and ambiguity — a builder, not just an operator

Demonstrates genuine commitment to responsible AI — not just checkbox compliance orientation

Attracts and develops exceptional talent; creates careers, not just roles

Strong executive communication skills — comfortable presenting to boards, CMOs, and CFOs with and without technical audiences

USD $225,000.00/Yr. USD $275,000.00/Yr.

SCA Health is building the data and AI foundation that will define its competitive position as the leading ambulatory surgery company in the United States. This is a greenfield executive leadership role — a chance to shape strategy, build a team, and establish the governance and technology platforms that will serve SCA's 300+ facilities and 12,000+ associates for the next decade. The VP, Data & AI reports directly to the CIO and is one of eight direct reports on the CIO's leadership team. You will own the enterprise data strategy, platform, and governance function, and will lead SCA's AI and machine learning capability — from foundational MLOps infrastructure through clinical decision support and operational AI at scale. This role sits at the intersection of healthcare's two most consequential technology shifts: the transition to data-driven clinical and operational decision-making, and the responsible deployment of AI in care delivery. You will work in direct partnership with SCA's CMO, CFO, COO, CGO, and clinical leaders — not just the technology organization.

Core Accountabilities:

Enterprise Data Strategy & Platform. Define and execute SCA Health's multi-year data platform roadmap — cloud data architecture, EHR/PAS data integration (HST, Athena, eCW, etc.), real-time pipelines, and the infrastructure that makes trusted data available to every decision-maker across the enterprise.

AI & Machine Learning Strategy. Lead SCA's AI roadmap — from MLOps infrastructure and model development through production deployment and monitoring. Prioritize use cases with rigorous business case analysis and establish clinical validation protocols.

Responsible AI & Ethics Framework. Establish SCA's responsible AI standards — model documentation, bias monitoring, explainability requirements, and the AI Review Board that ensures every clinical AI deployment meets the highest standards of safety and transparency. Track FDA SaMD guidance.

Cross-Functional Enterprise Partnership. Operate as the data and AI thought leader for the enterprise — partnering with VP Product on data-informed product decisions, with CISO on data security and AI risk, with Head of Architecture on platform design, and with clinical and operational leaders on use case identification and adoption.

Team Building & Talent Development. Build and lead a high-performing team of 12–15 data and AI professionals across six functional areas. Establish a culture of rigor, curiosity, and clinical partnership that attracts top talent in a competitive market.

Investment & Vendor Management. Own the Data & AI technology budget, vendor evaluation, and contract strategy. Make disciplined build/buy/partner decisions and defend investment priorities with rigorous ROI analysis to executive and board-level audiences.

Shared Accountabilities:

Data Governance & Quality. Support evolving SCA’s enterprise data governance framework — ownership model, data dictionary, quality standards, master data management, and compliance posture across HIPAA, TEFCA/HTI-1, and emerging interoperability mandates. Function currently reports to Sr. VP of Innovation.

What the role does not own:

Analytics & BI: Remains with the Payer Analytics team, not IT. VP Data & AI is an enabler of analytics capability — providing clean data, governed pipelines, and platform access — but does not own the Analytics & BI roadmap or outcomes.

Required Experience:

10+ years in data, analytics, or AI leadership roles, with 4+ years at VP or equivalent level

Demonstrated experience building enterprise data platforms at scale (cloud-native, modern data stack: dbt, Spark, Databricks or Snowflake)

Healthcare data experience required — EHR integration (HL7/FHIR), HIPAA compliance, clinical data structures and terminology

Hands-on experience leading AI/ML initiatives from business case through production deployment and ongoing monitoring

Proven track record building and leading high-performing technical teams of 10+ people in complex organizations

Experience establishing data governance frameworks in multi-site or distributed healthcare organizations

Preferred Experience:

Ambulatory surgery, surgical specialty, or multi-site healthcare network experience

Familiarity with FDA Software as a Medical Device (SaMD) regulatory framework for clinical AI

Experience deploying generative AI in enterprise or clinical settings (RAG pipelines, LLM evaluation, guardrails)

Track record of data product thinking — not just infrastructure, but data as a product consumed by business users

Graduate degree in computer science, data science, statistics, biomedical informatics, or related field

Experience operating in a PE-backed or high-growth acquisition-driven environment

Technical Depth Expected:

Cloud data platforms: Databricks, Snowflake, or Azure Synapse — architectural fluency required (not just familiarity)

Healthcare interoperability: HL7 v2, FHIR R4, SMART on FHIR — integration pattern experience

ML frameworks and MLOps: MLflow, Kubeflow, SageMaker, or Vertex AI

Data governance tooling: Collibra, Alation, or equivalent enterprise catalog platforms

BI and analytics: Tableau, Power BI, or Looker — platform strategy and semantic modeling

GenAI patterns: RAG architecture, LLM evaluation frameworks, prompt engineering at enterprise scale

Leadership Profile:

Equally fluent in the executive boardroom and the data architecture whiteboard — not one or the other

Build trust with clinicians and operational leaders; demonstrates clinical context, not just technical empathy

Makes decisions with data, not just instinct — models the culture they are trying to build

Comfortable with greenfield environments and ambiguity — a builder, not just an operator

Demonstrates genuine commitment to responsible AI — not just checkbox compliance orientation

Attracts and develops exceptional talent; creates careers, not just roles

Strong executive communication skills — comfortable presenting to boards, CMOs, and CFOs with and without technical audiences