AVAILABLE: ONLINE ON CAMPUS

At a Glance

  • 100% online coursework
  • STEM-designated by the US DHS
  • Project-based analytics capstone
  • Expert faculty in data science
  • No GMAT/GRE required

Flexible options to build advanced quantitative skills

The groundbreaking researchers in Pace’s Seidenberg School of Computer Science and Information Systems designed our 100% online MS in Data Science to equip professionals for the complex technical problems of an unpredictable world. This STEM-designated program delivers:
  • Advanced quantitative methods and best practices for data governance
  • Coursework that includes analysis, visualization, and machine learning
  • Competence in achieving organizational goals through data-driven approaches
  • Hands-on experience with real-world projects
  • Expertise to meet the growing demand for data scientist
You have the option 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. Along the way, you’ll work closely with Seidenberg School faculty, learning to develop vital insights through statistical programming, data management, and automation.
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To learn more about the online Master of Science in Data Science, fill out the fields in this form to download a free brochure. If you have any questions at any time, please contact an admission advisor at (866) 843-7205.

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Complete the Degree in 10 Courses

Become proficient in industry-standard tools to support daily operations and long-term strategic planning.

Personalize Your Degree

Choose from elective courses in fields such as computer science, information systems, business analytics, and natural sciences.

In-Demand Data Science Skills

Add expertise in machine learning, data mining, predictive analytics, advanced data management tools, and programming languages.

Course Highlights

Applied Artificial Intelligence

A survey of current technologies and future trends in artificial intelligence, including issues related to search algorithms, robotics, expert systems, and more.

Python Programming

Covers Python fundamentals with an emphasis on data analytics libraries. Learn to clean data, perform exploratory analysis, and build predictive models.

Machine Learning

Explores key learning theories (PAC, ERM, SRM, MDL) and algorithms (linear models, gradient descent, SVM, kernel methods, trees), in addition to advanced topics such as clustering, dimensionality reduction, generative models, and feature selection.

Learn From Top Thinkers in the Field

In the MS in Data Science program, you’ll take courses from researchers who contribute to pioneering work in fields such as artificial intelligence, software development, cybersecurity, machine learning, robotics, and computer vision. Through recorded lectures and live interactions, our faculty members bring groundbreaking insights into the virtual classroom and ensure that students are ready to take on emerging challenges in the field. Located in New York City, the world’s greatest hub for international business, Pace also offers the chance to connect and collaborate with industry experts who have evolved the field of data science. For more details, see our faculty page.
Mudassir Ali

“In my current role at Northwell Health, because I learned about model building at Pace University, I was able to pitch business problems that revolved around predicting modeling that I am currently working on. I was able to provide sound arguments to why we need this model, how it will affect the business approach, and how the company can benefit from it. Thus, being able to work on these models has brought a whole new level of analytics to my department at Northwell Health.”

Mudassir Ali (MS in Data Science 2022)

Data Scientist, Northwell Health

A Curriculum Designed for Quantitative Problem Solvers

The Seidenberg School has decades of experience offering fully online programs. 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. 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. Our data science master’s program is STEM-designated, indicating a curriculum focused on science, technology, engineering, and math that can lead to rewarding career opportunities. Visit our curriculum page to learn more.

Data Science Careers

As organizations strive to gain insights into their customers and supply chains or harness the latest advances in machine learning, they need highly skilled experts to collect, manage, and find meaning in their data. The U.S. Bureau of Labor Statistics projected a 35% increase in data science jobs over the next decade. Job posting data from the labor database Lightcast shows that the average salary offered for data scientists with a master’s degree is $140,200. Top skills employers request include machine learning, computer science, statistics, and the programming languages Python, SQL, and R. The top employers for professionals in this field include technical service providers, finance and insurance companies, healthcare organizations, manufacturers, and the information sector. Online master’s in data science graduates develop the background in quantitative analysis and interpretation to succeed in any of these roles:
  • Data Scientist
  • Data Analyst
  • Database Architect
  • Quantitative Analyst
  • Data Engineer
  • Machine Learning Engineer
  • Business Analyst
  • Software Engineer
  • Network Architect
For more information about career options, read our detailed article about what you can do with a master’s in data science.

Admission Requirements

Applications are carefully reviewed by the Graduate Admission Committee utilizing a holistic approach. To apply, you should have:
  • Bachelor’s degree in any field, with proficiency in calculus, linear algebra, some knowledge of probability and statistics, and some experience in programming and databases*
  • Minimum GPA of 3.0 preferred
*Students without the required background in programming and databases will be required to satisfy the prerequisite level of knowledge by completing online bridge courses in Database Management Systems and Python Programming once enrolled. For more details on admission requirements and the application process, visit our admission page.