Computational Science & Statistics - Data Science

The Computational Science and Statistics Ph.D. program is designed to train students to integrate computational and statistical methodologies to formulate, model, analyze, and solve research problems of interest in a wide variety of applied and theoretical contexts.  The Data Science Specialization will emphasize curriculum and research programs that prepare graduates to support local, regional, and national industry by analyzing large and complex datasets.

• Have an undergraduate or master's degree in mathematics, statistics, or related field
• Have strong problem-solving and quantitative skills
• Are able to grasp the essence of complex situations
• Have good communication skills
• Want your quantitative skills to have an impact

• A minimum GPA of 3.0 to receive unconditional admission. 
• A professional academic transcript evaluation for degrees earned outside the United States (This requirement cannot be waived unless your highest degree was earned or will be earned in the U.S. prior to enrollment at SDSU).
  • If you are completing your bachelor's degree at the time of application, you may submit an incomplete evaluation. If you are accepted, a complete transcript and/or evaluation with completed degree will be required by the end of your first semester of coursework.
• Official U.S. transcripts where a degree is earned (or will be earned), and official U.S. transcripts where graduate level coursework has been taken.
• A minimum TOEFL score of 71, TOEFL Essentials score of 7.5, IELTS score of 6 or Duolingo score of 100.
  • SDSU accepts MyBest TOFEL scores. 
  • Some programs have higher minimum requirements. Find program specific requirements by selecting your program of interest in the Graduate Catalog.

• Data scientist
• Predictive analyst
• Statistician
• Financial/business analyst
• Risk analyst
• Professor
• Researcher