Associate Vice President, Institutional Data Analytics - Office of Assessment and Decision Support (

Washington D.C
Apr 05, 2019
Jun 27, 2019
Full Time
Located in a historic neighborhood in the nation's capital, Georgetown offers rigorous academic programs, a global perspective, exciting ways to take advantage of Washington, D.C., and a commitment to social justice. Our community is a tight knit group of remarkable individuals interested in intellectual inquiry and making a difference in the world.


Associate Vice President, Institutional Data Analytics - Office of Assessment and Decision Support (OADS)

The Associate Vice President, Institutional Data Analytics is the leader of the Office of Assessment and Decision Support (OADS) . This data analytics department (OADS) at the university develops, uses, assesses and refines the university's data systems. These systems are used to assist key senior university decision-makers, from the President, Provost and C.O.O. to academic department chairs, as a source of data and analytical information critical to institutional decision-making. The Associate Vice President is responsible for leading the workforce within OADS, and for creating operating structures and systems that allow OADS to provide institutional research, reporting and predictive analytics resources.

Working closely with the Provost and the Main Campus Chief Financial Officer, as well as with leaders of UIS and other units, the AVP will serve as a liaison among various data stewards and sources across the university, and will oversee efforts to efficiently combine and aggregate data resources. S/he will advocate both for users of existing data, and for further development of the University's data systems and structures as more sophisticated tools for decision-making are created.

The AVP must have statistical skills of the highest caliber, with a strong command of data management, modeling and analysis, and visualization. However, as well as managing and integrating databases, and providing descriptive statistics about the university's student body and other activity indicators, a sound understanding of causal inference and the limitations of non-experimental data is required. To the extent that decision-makers need to understand the likely impacts of their decisions, the predictive information provided by OADS must at least acknowledge the inferential challenges that naturally arise in such contexts. Candidates that combine strong data skills with experience in the quantitative empirical social sciences, including for example economics, education, sociology, and public policy, would thus be well suited to the position.

  • 10 years' experience in statistical modeling, evidence-based decision support, analytics, data curation, and/or related consulting experience
  • M.A. in Data Science, Statistics, Economics, Computer Science, or another quantitative social science
  • Exceptional communications skills, both in written form and in and data visualization
  • Excellent leadership skills and experience in leading a small team
  • Experience at an educational institution is a plus, though not required

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