Master of Science in Data Science

The 100% online MS in Data Science was designed by the groundbreaking researchers in Pace’s Seidenberg School of Computer Science and Information Systems. In this program, you’ll prepare to start or advance your career in fueling innovation with advanced quantitative methods and best practices for data governance. Our flexible program makes it possible to take courses either full or part-time on a schedule that works for you. Part-time students can finish their master’s degree in two years while working, and full-time students can complete the program in a little over one year.

The Seidenberg School has decades of experience in offering fully online programs, dating back to 1999. Our data science curriculum channels that expertise to delve into both quantitative theory and practical applications. In seven required courses and three electives, you’ll explore best practices for managing, structuring, and finding valuable insights in data. In addition, you’ll gain hands-on experience with data mining techniques and writing algorithms.

The master’s in data science benefits students by expanding their knowledge of:

    • Python Programming
    • Machine Learning
    • Intro to Data Science
    • Scalable Databases
    • Algorithms for Data Science
    • Online Social Network Analysis

Focus on the topics that suit your career path by choosing electives in computer science as well as information systems, business analytics, and natural sciences. In the project-based Analytics Capstone, you can solve a real-world problem that interests you by conducting quantitative research and applying the data science methods you’ve learned in the program.


This program is STEM designated, which means you will be trained in areas of technology that are in high demand with United States employers.

It is preferable for students to have a background in computer science, mathematics, or statistics, and a desire to combine the skills of these fields. However, students with other bachelor degrees will be considered for the MS in Data Science based on their previous academic performance and experience.

Students must be proficient in calculus and linear algebra, and also have some programming and database experience.

View the curriculum worksheet (PDF) 


Admission Requirements 

Candidates are required to hold a four-year undergraduate degree or equivalent from a regionally accredited institution. A 3.0 undergraduate GPA is preferred, though we use a qualitative approach when looking at applications. Proficiency in calculus and linear algebra, some knowledge of probability and statistics, and experience in programming and databases is required.  

  • Students who do not meet the prerequisite level of knowledge for the MS in Data Science program are required to take two online bridge courses before starting the core/foundation curriculum:  
  • CS 623 – Database Management Systems 
  • CS 632P – Python Programming 


Admission Materials 

  • Completed online application 
  • Resume 
  • Two letters of recommendation (academic and professional) 
  • Personal statement 
  • Prerequisite courses or bridge courses upon entering the program 
  • Official college/university transcripts from all previously attended institutions 
  • GRE and GMAT scores are not required. 

Transcripts can be sent to: 

Pace University
Graduate Admission Office
Graduate Application Processing Center
One Pace Plaza
New York, NY 10038

Digital Transcripts can be sent to: 

Pace University 

International students must also submit: 

To satisfy the Proof of English Requirement, we will accept TOEFL, IELTS, Pearson PTE, or Duolingo academic scores. 

Data Science Careers

  • Data Scientist
  • Data Analyst
  • Database Architect
  • Quantitative Analyst
  • Data Engineer
  • Machine Learning Engineer
  • Business Analyst
  • Software Engineer
  • Network Architect

Tuition Summary

  • Required Credits: 30
  • Cost Per Credit: $951










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Stephanie Hsu, Associate Professor

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