Vice President Data and Artificial Intelligence

Responsibilities

• 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.

Qualifications

• 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 AIData 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.

Pay

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