Director of Data Operations, Analytics and AI Enablement

Overview

New York Institute of Technology's six schools and colleges offer undergraduate, graduate, and professional degree programs in in-demand disciplines including computer science, data science, and cybersecurity; biology, health professions, and medicine; architecture and design; engineering; IT and digital technologies; management; and energy and sustainability. A nonprofit, independent, private, and nonsectarian institute of higher education founded in 1955, it welcomes nearly 8,000 students worldwide.

The university has campuses in New York City and Long Island, New York; Jonesboro, Arkansas; and Vancouver, British Columbia, as well as programs around the world. More than 112,000 alumni are part of an engaged network of physicians, architects, scientists, engineers, business leaders, digital artists, and healthcare professionals. Together, the university’s community of doers, makers, healers, and innovators empowers graduates to change the world, solve 21st-century challenges, and reinvent the future.

For more information, visit nyit.edu.

New York Institute of Technology seeks a dynamic and strategic Director of Data Operations, Analytics and AI Enablement to lead the design, development, implementation and ongoing maintenance of NYIT’s data and an AI strategy to include analytics, t infrastructure, and AI capabilities. This hands-on leader will collaborate with cross-functional teams, provide day-to-day technical guidance and direction, establish strategic plans for data ecosystem modernization efforts, and oversee the integration of AI-driven solutions into data processes, enhancing analytics capabilities and operational efficiencies. The ideal candidate will bring deep expertise in both operational and strategic aspects of data and AI enablement. This role is critical to advancing NYIT’s data-driven and AI-supported initiatives, supporting the institution’s mission of educational innovation and excellence.

Responsibilities

• Develop and lead a comprehensive data strategy aligned with NYIT’s academic and operational goals and modern industry standards; partner with stakeholders to prioritize and manage data-related initiatives ensuring alignment with institutional strategies and objectives.
• Drive the development of analytics and analytics capabilities to support informed decision making across the campus; oversee the creation and maintenance of dashboards, reports, and analytics tools that provide actionable insights; identify and adopt viable trends and areas for improvement.
• Oversee and complete migration of the on-premise data warehouse and BI toolset to a scalable cloud-based model; manage data access and data governance across all users; provide expertise and support in data visualization and self-service access; devise a strategy for enterprise reporting, operational analysis, and advanced analytics that supports a single, authoritative source of truth.
• Develop and maintain a robust and modern data architecture for analytics, transactional data and master data to support both data exploration and analytics.
• Develop and execute a comprehensive strategy for AI adoption and integration across the university to enhance academic, administrative, and student engagement outcomes; identify opportunities to leverage AI technologies to advance institutional goals, improve operational efficiency, and enhance student success initiatives; and serve as a thought leader on AI trends and their implications for higher education, advising university leadership on emerging technologies.
• Lead the development and deployment of AI-driven solutions for personalized learning, academic advising, operational efficiency, student engagement, research, and more.
• Collaborate within IT, academic, and administrative teams to integrate AI into existing systems, such as learning management systems (LMS), ERP, CRM, and student success platforms.
• Identify and coordinate the correction of bad data, ensuring data integrity issues are escalated to the proper responsible parties, addressing data issues at the source; locate, define, and communicate recommended process improvements and issues to key internal and external resources regarding data quality.
• Work with the Data Governance Council to evaluate and implement data governance policies, ensuring data quality, security, privacy, and compliance; ensure data and AI projects adhere to best practices in data governance, security, and privacy, including compliance with FERPA, GDPR, and other regulations.
• Promote clear communication of enterprise design/development approaches, workflow and data standards, and reporting/BI requirements; review documentation developed by other departments to ensure adherence to data standards and consistency of information to analysts and developers; modify documentation and training materials as nece