Ph.D. in Statistics & Data Science

Regular Track and Informatics Track PhD

The interdisciplinary nature of the PhD programs in Statistics & Data Science allow students to customize their degree program in order to combine their interests and their career objectives. 

Put simply, statistics is the science of data. It employs mathematical relationships about probability and uncertainty to understand the underlying phenomena, and is an exciting area of growth in our modern society.

Graduates of the Statistics & Data Science PhD program work in academia and in industry.  There are huge opportunities in all industries for statisticians.

The average time to completion for a Ph.D. in Statistics & Data Science is 5.49 years.

First, you apply to the program.  Once you have been recommended for admittance you will automatically be considered for a teaching assistantship.

While an undergraduate or MS degree in Statistics is beneficial, it is not required.  See the Admissions page for more information on the admissions requirements.

Here is a partial list of where recent Phd graduates began their careers:

  • Allen Institute
  • Abbvie
  • California State University at Chico
  • Critical Path Institute
  • Raytheon
  • University of Vermont
  • Bio5 Institute University of Arizona
  • Wish
  • Oberlin College
  • University of Nevada, Reno
  • Ventana Medical Systems
  • Tennessee Health Center
  • University of Rochester

To see the coursework requirements go to the Coursework Requirements page on the SDS GIDP website. 

All students entering any Statistics & Data Science Program are required to have a substantive background in mathematics, including at least three semesters of Calculus through multivariable/vector calculus, one semester of Linear Algebra, and experience with computer technologies.

Go to the Admissions Requirements page on the SDS GIDP website.