BY Meghan MalasJuly 27, 2022, 6:13 PM
Members of the student section wave Fighting Illini orange foam noodles during a Big 10 Conference match-up between the Northwestern University Wildcats and the University of Illinois Fighting Illini, as seen in February 2022, at the State Farm Center in Champaign, Illinois. (Photo by David Allio—Icon Sportswire/Getty Images)
Data science is a burgeoning field, and over the past decade, universities have been developing academic programs to help meet the demand for data-savvy graduates. Online master’s degree programs in data science allow even more prospective students access to skills that can land them a high-paying, rewarding job.
As Fortune reported in May, the University of Wisconsin-Madison’s undergraduate major in data science is the fastest-growing and fourth-largest major on the campus—a key reason why the university decided to launch a master’s degree program in the field later this year.
Many online master’s in data science programs don’t require applicants to submit GRE scores—a trend that has also been seen in online MBA degree programs. Nixing GRE requirements eliminates a potential barrier to entry for applicants, but it also tasks schools with relying on other metrics and qualifications to determine a student’s readiness for the program.
But it’s not just a COVID-19 phenomenon that’s causing test policy changes. In February 2020, the University of California—Berkeley announced it was making standardized test scores optional for its data science degree programs, following a recommendation made by the School of Information’s diversity working group.
“A detailed review of relevant research indicates that standardized graduate entrance examinations are weak predictors of academic success in graduate school and that overemphasizing GRE and GMAT scores replicates and amplifies structural disadvantages to some demographic groups, particularly students from underrepresented minority and lower socioeconomic backgrounds,” according to the announcement.
Fortune reached out to the top-ranked online master’s in data science schools that don’t require the GRE to find out more about their application processes and programs.
1. University of Illinois at Urbana—Champaign
The University of Illinois at Urbana—Champaign launched its master’s degree program in data science in the fall of 2016 and it has never required applicants to submit GRE scores.
“Around 2015 and 2016, the impact of data science, machine learning, and more generally of data driven computation, was becoming evident,” says Mahesh Viswanathan, a computer science professor and associate head for academics at the University of Illinois at Urbana—Champaign.
The degree program was created for busy professionals who want to earn a graduate degree in data science, all while maintaining their current life and career obligations.
“A majority of our students are already working in the industry but are seeking to gain knowledge to facilitate a promotion, lateral move, or switch employment,” Viswanathan says.
The university’s data science courses aim to give students a solid footing in the foundations of data science, all while being exposed to its applications across various industries. “We have unique courses in our program—like deep learning for healthcare and computational photography—that are unlike courses in any other academic program,” Viswanathan says
2. University of California—Berkeley
The University of California, Berkeley’s School of Information began offering an online master’s degree program in information and data science in 2014.
“The program was designed to equip working professionals with the tools and knowledge to analyze, store, process, visualize, and use the increasing quantity of data and datasets available across a wide variety of industries,” says Catherine Cronquist-Browning, the school’s assistant dean of academic programs and of equity and inclusion. “We saw a significant need to prepare a new group of skilled leaders who could meet the needs of this exciting moment in technological development.”
From the beginning, the program required applicants to submit GMAT or GRE scores. But test scores became optional after the Spring 2020 term.
“We’ve found over time that a holistic admissions process, in which we de-emphasize standardized test scores and evaluate applicants comprehensively across a variety of dimensions, is the most beneficial both for our program and for applicants,” Cronquist-Browning says.
The online courses are offered live, and are intended for students with a high level of quantitative ability, a problem solving mindset, and the ability to communicate effectively. On average, students have about five to eight years of prior work experience before enrolling.
“However, we’ve also had students successfully complete the program without prior work experience,” Cronquist-Browning says. “The program is well-suited for professionals already working in data science, data analysis, and related fields who want to increase their knowledge and skills, as well as for people making a career transition into data science.”
While UC Berkeley intentionally tries to keep section sizes small—to about 15 students—the program’s duration allows them to have access to a large alumni network of over 1,400 graduates. “We pride ourselves on having a robust curriculum that considers the broader societal impact of data science and legal, policy, and ethical issues throughout the full data-science life cycle,” Cronquist-Browning tells Fortune.
3. Texas Tech University
Texas Tech University suspended the requirement of GMAT and GRE scores in the 2020-2021 academic year for the master’s degree program in data science program due to the COVID-19 pandemic, according to the program’s webpage.
Additionally, test score requirements are waived for applicants who have five or more years of relevant work experience. Students who entered the program in Summer 2020 had an average of nine years of work experience.
While no prior work experience is required, the program’s website notes that most applicants have an education or work background in computer science, management information systems, science, engineering, or similar fields—and a basic knowledge of computer programming software.
4. Bay Path University
Bay Path University created its online master’s in data science program in 2016, and it never required applicants to submit GRE scores.The 10-course, 30-credit program also doesn’t require students to have an undergraduate degree in any science or engineering field.
“This fully online program was created for working professionals looking to become data scientists, data analysts or business analysts—or just people looking to incorporate data analysis into their current role,” says Xiaoxia Liu, director of the applied data science program.
The program offers two tracks. This first is a generalist track which focuses on the skills needed to be a successful data analyst or data scientist, regardless of a student’s background or previous expertise. The second track prepares students for more technical roles on data science teams; positions like data mining engineer or data warehouse architect.
“Our data science courses are small and taught by faculty from academia and the industry,” Liu says. “And our job placement rates are great—combination of the motivation our students possess, the coursework and learning they’re exposed to, and the high demand for these skills.”
5. Worcester Polytechnic Institute
The online master’s in data science degree program at the Worcester Polytechnic Institute was launched in 2018 and never required applicants to submit GRE scores.
“From the start, we have found that the GRE scores are not a reliable indicator of someone’s potential to excel in our graduate degree program,” says Elke A. Rundensteiner, a professor and founding director of the data science department. “Instead, both courses taken and grades in their undergraduate degree—as well as relevant professional experiences—are much better indicators of someone’s readiness for succeeding in the data science degree program at WPI.”
The data science program emphasizes skills in computer programming, artificial intelligence, data cleaning, machine learning and deep learning, big data management, statistics, cloud computing, and visualization, through both course work and hands-on projects. Graduates from the program typically go into roles like data scientist, data engineer, data analyst, business analyst, database administrator, or data architect.
“Our program prepares the student to derive new insights from data and articulate these findings into innovative solutions for how we live, work, and interact with the world around us,” Rundensteiner says.