On of the best jobs in America, according to Glassdoor.

Located in San Francisco, Pacific's MS in Data Science program equips students for the exciting field of data science. This STEM-designated program uses a hybrid approach to learning with most courses requiring attendance in both in-person and online class sessions. It consists of 4 semesters spread over 2 academic years, during which 32 units must be completed for degree conferral. Starting in Fall 2019, each unit costs $1,498. Our students receive a personalized education featuring the small class sizes that are a trademark of a Pacific education.

Data scientists are in high demand. Every industry realizes that data is the key to future success, and organizations are looking for data scientists with deep knowledge of analytics. Pacific's Data Science program will prepare its students to be the data scientists of tomorrow. 

COVID-19: The MS Data Science Program WILL run this fall, as usual. We will have procedures in place to enable those students who cannot get to San Francisco due to travel/visa restrictions, to start their program online until travel restrictions are lifted. We will be following all official guidelines, including social distancing on our campus, to ensure everyone's health and safety.

Are you a Pacific undergraduate student? Consider adding the Minor in Data Science to your diploma. In addition to giving you highly-sought skills in Data Science, this is an excellent way to prepare for our Masters program in Data Science. For more info, visit the Minor in Data Science Webpage or contact the minor advisor, Prof. J. Hetrick.

Class of 2018
Alex Katona

"The program is intelligently designed for working professionals. I could continue to work full-time while taking classes full-time. This is possible because the in-person classes are held on Saturdays and the online classes are held after office hours. For my capstone project, I got to work with Charles Schwab, which helped me apply everything I'd learned in the program—something very few universities offered. I would strongly recommend this program to anyone considering a career in data science or advancing within the field."

Alex Katona at the San Francisco campus.

Select the link below to take the self-assessment test. This will help you determine if you have the necessary pre-requisite skills to start the Data Science program:

MS Data Science Self-Assessment

  • Bachelor's degree in any field
  • Must have coursework or experience in:
    • Linear algebra
    • Statistics-
    • Programming in a high-level language (experience in R and Python preferred)

  • Transcripts (1)
  • Two letters of recommendation
  • Resume
  • Statement of interest (2)

Neither the GRE nor the GMAT is required for admission to this program. 

  • Must have the U.S. equivalent of a 2.65 GPA to be eligible for admission to the program.
  • Must provide an official, course-by-course evaluation of their transcripts with an overall U.S. GPA equivalent from one of the agencies accepted by the University.
  • Must provide official English proficiency test scores from either TOEFL or IELTS.

Note: Course-by-course evalutions (and any other documents that are not directly loaded via GradCAS) should be sent to the following address:

University of the Pacific
Knoles Hall Second Floor, Room 207 B
3601 Pacific Avenue Stockton, CA 95211-0110 

  • An official set of transcripts from each institution you have attended is required as part of the application.
  • The statement of interest allows applicants to demonstrate their motivation, skills, and abilities that will contribute to their academic success in our program. While there is no specific format required for this statement, applicants are advised to give particular consideration to: o
    • Academic credentials
    • Experience in the foundational concepts of:
    • Statistics o Linear Algebra
    • Computer programming (any language, but Python and R are preferred)
    • Commitment and personal stamina to undertake fast paced, intensive academic program
    • Enthusiasm for this particular course of study

Contact Us

Engineering students with Professor
School of Engineering and Computer Science
(209) 946-2992