Senior Director, Data Analytics & AI Engineering

OhioHealth•Columbus, OH

22h•Hybrid

About The Position

The Senior Director of Data Analytics & AI Engineering leads a major function within OhioHealth’s technology organization, providing direction through subordinate managers across data engineering, data science, and data governance. This role is accountable for strategy, business planning, budgets, staffing, quality, compliance, and delivery outcomes, while partnering with technology, operational, and clinical leaders to modernize platforms, advance AI-enabled capabilities, and ensure data assets support enterprise, operational, and patient care priorities across the system. This is a hybrid position in Columbus, OH.

Requirements

Master's Degree: Computer and Information Science
Master’s degree (or experience in lieu of) in data related fields like Analytics, Data Science, Computer Science with knowledge of healthcare operations or significant experience in healthcare operations with a quantitative mindset.
Strong knowledge of the requirements, risks and opportunities around deploying data science, ML and AI at scale.
Strong knowledge and experience in transforming technical landscapes to adapt the needs of the business and to seize the value creation potential of data and data platforms.
Proven experience with leading transformational change.
Excellent leadership and communication skills, with proficiency across hierarchy and function.

Nice To Haves

Prior experience at data platform modernization and cloud enablement

Responsibilities

Lead execution of the data, analytics, and AI engineering strategy, translating OhioHealth priorities and technology direction into operating plans, investment priorities, and measurable outcomes.
Direct long-range planning, architecture, and resource allocation for enterprise data engineering, data science, and governance capabilities to ensure scalable, secure, and high-performing platforms.
Develop annual business plans, operating objectives, and portfolio priorities aligned to long-term functional strategy, enterprise business needs, and measurable performance expectations.
Lead the function through subordinate managers and senior leaders across data engineering, data science, and data governance, with accountability for team performance, staffing approaches, operating discipline, and coordinated execution across multiple teams.
Sponsor modernization of the data and AI technology landscape and establish operating standards, engineering practices, and support models that strengthen reliability, scalability, and execution consistency.
Ensure data and AI solutions are implemented, supported, monitored, and continuously improved in ways that enable durable adoption, operational performance, and enterprise value realization.
Partner with Technology Delivery, Data & Analytics, Epic, Digital, Security, and operational leaders to align priorities, implementation sequencing, platform readiness, and delivery expectations.
Partner with business, clinical, and operational stakeholders to define desired outcomes, shape solution priorities, and operationalize data and AI capabilities that improve decision-making, workflows, and performance.
Shape executable roadmaps and guide governance and investment decisions in partnership with enterprise strategy, architecture, finance, and operational leadership.
Ensure strong data quality, integrity, reliability, and stewardship practices across engineering efforts in partnership with governance and platform teams.
Partner with cybersecurity, privacy, and compliance leaders to embed security, regulatory, and responsible use requirements into data, analytics, and AI solutions.
Support enterprise governance, prioritization, and decision forums that promote disciplined use of data assets, clear standards, and consistent execution across the portfolio.
Strengthen organizational capability by developing leadership depth, technical expertise, and data and analytics literacy across teams and stakeholder groups.
Serve as a trusted partner to senior leaders, providing clear insight into portfolio priorities, delivery progress, risks, and opportunities to support informed enterprise decision-making.
Responsibilities require focus on safety, quality and efficiency in performing job duties.