Data Science
The digitization of information—social networks, business transactions, healthcare records and more—has transformed the world, necessitating a demand for people who understand all of the big data being collected and who can take action to help individuals, corporations and organizations become smarter, faster and ultimately more effective.
Through Drew’s Master of Science and graduate certificate programs in Data Science, you will:
Read more about the Data Science degree, and review the Program Requirements.
Email: sabramow@drew.edu
Office: HS 312
Phone: 973-408-3346
Sarah Abramowitz earned a BA in Mathematics from Cornell University, an MS in Mathematics from the State University of New York at Stony Brook, and a PhD in Mathematics Education from New York University. Dr. Abramowitz has been a professor in the Department of Mathematics and Computer Science at Drew University since 1998. She specializes in Educational Statistics. She is the co-author with Sharon Weinberg of “Statistics Using IBM SPSS: An Integrative Approach,” “Statistics Using Stata: An Integrative Approach,” “Statistics Using R: An Integrative Approach,” and serves as an Associate Editor and Social Media Editor of the Journal of Statistics Education.
Bio to come.
Email: dliporace@drew.edu
Diane Liporace earned a M.S. in Computer Science from Montclair State University, and received a B.S. in Mathematics with a minor in Computer Science from Mercy College. She is co-author of a research paper, Urban Legislation Assessment by Data Analytics with Smart City Characteristics. In 2017, she joined the Department of Mathematics and Computer Science at Drew University as an adjunct instructor.
Email: ylu1@drew.edu
Office: HS 309
Phone: 973-408-3769
Yi Lu received a Ph.D. in Statistics from the Ohio State University in 2017. She has taught a few undergraduate classes at Ohio State and worked as a statistical consultant on various research projects with graduate students from other disciplines. She studied both History and Mathematics as an undergraduate (Mars Hill University, North Carolina) and enjoys using statistics in very diverse applications. Her current research interests include Bayesian methods, functional data, and curves and images. She recently moved to New Jersey and loves running in her spare time.
Elizabeth Pemberton received a BA in Physics from Drew University and an MS in Applied Mathematics and Statistics from Stony Brook University. Elizabeth is currently a PhD Candidate in Data Science at Northcentral University. Her research is in the field of computational content analysis and focuses on using a combination of network analysis, natural language processing, and computer vision to programmatically evaluate representation across hundreds of films from the past 40 years. Elizabeth also has five years of experience as a full-time data scientist and currently works at a New York City startup as a senior data scientist. When she’s not thinking about the ways she can use data science to quantify the realities of our world, Elizabeth enjoys playing video games on her playstation, building 3D puzzles, and reading science fiction.
Alex Rudniy earned his PhD in Computer Science from New Jersey Institute of Technology in 2012.Before joining Drew, he taught courses at University of Scranton and Fairleigh Dickinson University. He earned his MS and BS in Applied Mathematics at National University of Radio Electronics, Ukraine. Dr. Rudniy’s research interests are in artificial intelligence, machine learning, natural language processing, time series forecasting, cybersecurity and the amalgamation of the above. Dr. Rudniy enjoys spending time outdoors doing hiking, biking, kayaking, swimming, or fishing.
Ellie Small received a BSc degree in Mathematics with Statistics and Computer Science from the University of London, Birkbeck College. She earned her PhD in Statistics from Rutgers University, New Brunswick, in 2019, and joined the Department of Mathematics and Computer Science at Drew University that same year. Dr. Small has taught statistics and mathematics at Centenary University in Hackettstown for 6 years. She specializes in data science and has completed research papers in networks and text mining. In her spare time she enjoys any type of dance, and she goes ballroom dancing with her husband whenever the opportunity presents itself.
Drew’s Data Science programs are structured to focus on the intersections of statistics, computer science, skills and technologies. ”
Both our 12-credit certificate programs and our 30-36 credit Master of Science degree will prepare you to become an advanced analyst who can create and develop data sets and analytic protocols, communicate your analytic findings to leaders and general audiences and ultimately participate in data-informed decision making.
The examples for the course of studies below are for full-time programs, but part-time options are also available.
Foundational courses (6 credits)
Must be taken prior to enrolling in core courses. May be taken during the summer before the program starts.
Fall (12 credits)
Spring (12 credits)
Summer (6 credits)
View the Course Catalog for more details.
Foundational courses (6 credits)
Must be taken prior to enrolling in core courses. May be taken during the summer before the program starts.
Fall I (6 credits)
Spring I (6 credits)
Fall II (6 credits)
Spring II (6 credits)
Summer (6 credits)
View the Course Catalog for more details.
Foundational courses (6 credits)
Must be taken prior to enrolling in core courses. May be taken during the summer before the program starts.
Spring I (6 credits)
Fall I (9 credits)
Spring II (6 credits)
Summer (6 credits)
Fall II (3 credits)
View the Course Catalog for more details.
Our graduate certificates enhance core skills required to draw information from data. You may choose from one of three emphases: Statistics, Data Science or Business Analytics. Or, design your own program in consultation with the program director. If you complete one of these certificate programs, you may apply the credits to the Master of Science in Data Science.
Prerequisites (6 credits)
Must be taken prior to enrolling in a Data Science certificate program. May be taken during the summer before the program starts.
Data Science Certificate: Statistics (12 credits)
View the Course Catalog for more details.
Data Science Certificate: Data Science (12 credits)
View the Course Catalog for more details.
Data Science Certificate: Business Analytics (12 credits)
View the Course Catalog for more details.
With the digital transformation of academia and the workforce, it is not surprising that data science and data analytics jobs are projected to grow at some of the fastest rates in the near future.*
Job title | Average salary | Projected five-year growth |
Analytics managers | $105,909 | 15% |
Data scientists & advanced analysts | $94,576 | 28% |
Data-driven decision makers | $91,467 | 14% |
Data systems developers | $78,553 | 15% |
Data analysts | $78,553 | 16% |
Functional analysts | $69,162 | 17% |
*Burning Glass Technologies
Contact us to learn more about the Data Analytics program.
Start terms: Fall or spring
Deadline: Rolling admissions
Admission requirements
- Completed application
- Bachelor's degree from an accredited institution with a 3.0 GPA
- Official transcripts from all post-secondary institutions
- Personal statement
- Resume/CV
- GRE or GMAT scores optional
INTERNATIONAL APPLICANTS
need to meet additional criteria, such as submitting TOEFL/IELTS scores. See our international admissions page for more information