Henry Schein · 23 hours ago
Executive Director, Data, Machine Learning & AI
American Fork, UT
Full-time
Onsite
Director/Executive
15+ years expHenry Schein is a global leader in healthcare technology, and they are seeking an Executive Director to lead their initiatives in Big Data, Data Science, and Machine Learning. The role involves setting enterprise data and AI strategy, overseeing data platform evolution, and ensuring compliance while delivering measurable business outcomes through data products and ML/AI solutions.
DentalHealth CareMedical Device
Responsibilities
Set enterprise data & AI strategy in coordination with Leadership that aligns to company and product strategies; define a 2–3 year roadmap for data platforms, analytics, ML/AI capabilities (including GenAI), and business value realization
Deliver on the data platform (data lake/lakehouse, warehouses, streaming) evolution; ensure scalability, reliability, cost efficiency, and performance across our cloud environments. Architecture will be owned by the Architecture team, so a close working relationship is necessary
Establish and chair data & AI governance (policies, standards, data contracts, model governance), balancing innovation with risk, privacy, and regulatory compliance (e.g., HIPAA, GDPR/CCPA)
Operationalize MLOps/LLMOps: implement reproducible model lifecycle management (experimentation, approval, deployment, monitoring, drift/evals, rollback), feature stores, CI/CD, and automated observability
Drive GenAI adoption responsibly: identify high value use cases, build/reuse LLM platforms (RAG, vector search), set prompt/eval standards, safeguard IP/PHI, and manage content/usage policies and human in the loop controls. Much of this workstream will be in tight coordination with the office of our CISO
Deliver measurable business outcomes via data products and ML/AI solutions; prioritize the portfolio, define KPIs/OKRs with business owners, and track ROI, adoption, risk, and quality
Lead a multidisciplinary organization (data engineering, platform, analytics, data science/ML, data governance, AI product) with clear operating mechanisms, talent strategy, and succession plans
Partner with Security, Legal, Compliance, and Risk to implement privacy by design, model risk management, third party risk, and audit readiness; ensure encryption/IAM, data retention, and lineage are enforced
Advance data quality: institute golden sources, data stewardship, data quality SLAs, and remediation workflows across domains
Embed architecture standards and patterns: event-driven data, streaming (e.g., Kafka/Kinesis), APIs, data mesh/data product patterns, and zero ETL/ELT best practices
Manage vendor and partner ecosystem: evaluate/contract platforms and model providers, negotiate commercial terms, and ensure interoperability and exit options
Own financials for the function: plan budgets, forecast run/transform costs, optimize cloud spend (FinOps), and reinvest savings into innovation
Champion change management: communicate vision and progress to executives and broader teams; create communities of practice and playbooks to scale adoption
Ensure resilience and continuity: architect for HA/DR, data protection, backup/restore, and incident response for data and AI systems
Represent the company externally where appropriate (industry forums, academia, standards bodies) to attract talent and shape best practices
Qualification
Required
15 years of related experience with 7+ years in leadership/team management
Data Architecture: Lake/lakehouse and warehouse design; dimensional/semantic modeling; data product architecture; data mesh and data contracts
Cloud Data Platforms: Deep experience with one or more of AWS (S3, Glue, EMR, Redshift, Lake Formation), Azure (ADLS, Synapse, Fabric), Snowflake, and Databricks; multicloud patterns and connectivity
Streaming & RealTime: Event-driven design, CDC, and stream processing (e.g., Kafka/Kinesis, Spark Structured Streaming, Flink); lowlatency serving layers
Data Engineering Excellence: ELT/ETL frameworks, orchestration (Airflow/Databricks Workflows), metadata/lineage (OpenLineage), partitioning, performance tuning, and cost optimization
Analytics & BI: Metric stores/semantic layers, governed selfservice, embedded analytics, and A/B testing/experimentation frameworks
Machine Learning Fundamentals: Feature engineering, model development for classical ML and deep learning, offline/online feature stores, model packaging, and reproducible experimentation
MLOps/Model Governance: CI/CD for ML, approval gates, automated evaluations, drift detection, bias/fairness testing, explainability (e.g., SHAP), model catalog/registry, and monitoring/alerting
Generative AI & LLMs: Model selection (open/hosted), prompt engineering, RAG architectures, vector databases, policy/guardrails, redteaming, hallucination mitigation, and LLM evaluation metrics
AI Safety, Privacy & Compliance: Privacybydesign, PHI/PII handling, HIPAA and global privacy regulations (GDPR/CCPA), dataset provenance, copyright/IP controls, and secure isolation for training/inference
Security for Data & AI: IAM/leastprivilege, key management and encryption (at rest/in transit), secrets management, network segmentation, and secrets scanning; secure supply chain for data/ML artifacts
Data Governance & Quality: Stewardship operating model, profiling and rules, DQ SLAs, remediation workflows, golden sources/MDM, and business glossary/catalog (e.g., DataHub/Collibra/Purview)
AI/ML Product Management: Usecase discovery, value hypothesis and ROI modeling, stakeholder alignment, roadmapping/prioritization, and change management for adoption
SRE/Platform Reliability: SLOs/SLIs for data and ML services, capacity planning, HA/DR patterns, cost/perf telemetry, and incident management
Integration & APIs: Contract first API design, data services for operational systems, and secure interoperability with SaaS/ISVs
Financial & Commercial Acumen: TCO modeling, FinOps for data/AI workloads, license/subscription governance, and scalable chargeback/showback
Leadership & Talent: Organization design, hiring and coaching for data/ML/AI roles, vendor/partner management, and building communities of practice
Communication & Influence: Executive storytelling with data, risk/benefit framing, and the ability to align diverse stakeholders on standards and tradeoffs
Preferred
Bachelor's or Master's Degree in a related field preferred
Benefits
Medical, Dental and Vision Coverage
401K Plan with Company Match
Paid Time Off (PTO)
Paid Parental Leave
Short Term Disability
Work Life Assistance Program
Health Savings and Flexible Spending Accounts
Education Benefits
Worldwide Scholarship Program
Volunteer Opportunities
And more
Company
Henry Schein
Henry Schein is a provider of health care products and services to office-based dental, medical and animal health.
10001+ employees
H1B Sponsorship
Henry Schein has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (10)
2024 (5)
2023 (6)
2022 (6)
2021 (1)
2020 (7)
Funding
Current Stage
Public CompanyTotal Funding
$1BKey Investors
Kohlberg Kravis RobertsSMILE Health
2025-01-29Post Ipo Equity· $250M
2023-08-08Non Equity Assistance
2023-07-11Post Ipo Debt· $750M
Leadership Team
James A. Harding
SVP & CTO
Michael Ettinger
Executive Vice President, Chief Operating Officer
Recent News
Medical Product Outsourcing
2026-01-16
2026-01-16
Digital Commerce 360
2026-01-16
Company data provided by crunchbase