Provide leadership and expertise in advanced, cross-functional data analytics to deliver actionable analyses that drive Global Enrollment Management and Student Success (GEMSS) business processes and answer strategic questions about impact, outcomes, and future trends. Develop strategy to analyze, forecast, and visualize all aspects of enrollment management data including student recruitment activity, financial aid information, retention rates, student success metrics, as well as operational and customer service data to enable decision making and recommend changes in processes, policies, and technologies. Partner with the AVP of Enrollment Strategy to lead and manage analytics activities, ensuring alignment with University-wide strategic goals. Advise on best practices for external data reporting, ensuring compliance with industry standards, institutional policy, and data integrity and governance. Provide custom reports and conduct comprehensive analyses of external data sources, including competitor groups, publicly available datasets, and national rankings to benchmark the University’s standing relative to peer institutions, identifying opportunities for improvement and growth in enrollment processes and outcomes. Supervise two Data Modeling analysts to improve predictive models, enrollment forecasts, and other analytics tools. Ensure that data models reflect evolving institutional needs and market conditions, and drive continuous improvements in data accuracy and relevance. Stay informed about trends in artificial intelligence, machine learning, and other emerging technologies that could enhance data analysis and decision-making within the enrollment management space. Provide recommendations on the potential applications, risks, and benefits of integrating AI into enrollment processes, data analysis, and predictive modeling.
