Online Data Science Master’s – Guide to Choosing a Program

If you’ve worked your way through the difficult process of choosing where you’d like to focus your efforts in the field of data science, there’s one more important decision you still must make: where you’ll receive your master’s degree.

A master’s degree is all but officially a requirement to enter the field of data science competitively.

Without a data science master’s, it’s difficult to show prospective employers your expert skills and the knowledge you bring to the table.

FIND SCHOOLS

Why pursue a career in data science?

It’s no secret that the field of data science is a popular choice for many entering the job market at this time. Indeed, it’s an excellent choice to plot a career path, boasting high salaries and a remarkably high job growth estimate. Many are getting their data science degrees to take advantage of this booming industry, which promises to continue for years to come.

The numbers confirm that a career in data science is sure to be lucrative and viable in the long-term. The Bureau of Labor Statistics reports an impressive median annual salary of $100,910, significantly higher than average salaries elsewhere. This number is even higher in the top-paying industries for data scientists, which boast a mean annual salary ranging from $124,440 (in services related to accounting, tax preparation, and payroll) to a whopping $148,290 (in computer and peripheral equipment manufacturing). These terrific salaries reflect how valuable the skills and insights of a data scientist are to businesses of all kinds.

What’s more, based on our rising dependence on data, job opportunities for data scientists will only continue to grow in the years to come. Indeed, recent developments in machine learning mean that companies are now capturing more and more data, which in turn creates a need for more data scientists to help store, process, and translate this information so that businesses can make use of it. The Bureau of Labor Statistics is optimistic about job growth for data scientists, reporting a predicted job growth rate of 36% by 2031, a tremendous estimate that vastly exceeds numbers for most other job titles.

If you have an aptitude for computer science or statistics, these numbers should help entice you to pursue a career path in this flourishing industry.

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School Rankings
6 Steps to Choosing an Online Data Science Master’s Program
Timeline for an Online Master’s in Data Science
Signs of a Strong Data Science Program
Admission Criteria and Curriculum
Top Careers
Pros and Cons of Online vs. Campus
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Complete School Listings

Featured Programs:

School Rankings

When it comes to choosing an online master’s in data science, accept only the best.

The below list was carefully reviewed and ranked based on factors most important to students.

You will find a profile for each of the 15 ranked schools including information specific to the course of study, admissions requirements, and career support.

Finally, a link directly to the schools data science program website is included in the event you want to explore a specific school further.

Top 15 Ranked Online Master’s in Data Science Programs

1
University of Illinois at Urbana-Champaign – Champaign Illinois
The University of Illinois at Urbana-Champaign topped our list of data science programs. Their Master’s of Computer Science in Data Science has earned a strong academic reputation by featuring faculty members known for significant research accomplishments in the field of data sciences. Notably, the tuition cost was the lowest of the top 15 schools in this ranking. This combination of a strong reputation with value helped earn them the number one spot.
Course of Study
The University of Illinois at Urbana-Champaign offers a fully online Master’s of Computer Science in Data Science that fosters expertise in four core areas: data visualization, machine learning, data mining and cloud computing. Students also are able to enhance their skills in statistics and information science through courses taught in collaboration with the University’s Department of Statistics and School of Information Sciences, such Bayesian modeling, data curation, and a final capstone project. The 32 credit hours required for graduation can be completed in as little as 1 year or as long as 5 years.
Admissions Requirements
Prospective applicants must have received a 4-year bachelor’s degree equivalent to that granted by the University of Illinois before becoming eligible for the Master’s in Computer Science Program. In addition, applicants must have held a GPA of 3.0 or higher for the last two years of undergraduate study. Students with bachelor’s degrees in fields other than computer science are expected to have sufficient backgrounds in computer programming, data structures and algorithms, computer architecture, and theory of computation. The University recommends that applicants complete this coursework before submitting an application. Applicants from degrees outside of computer science and without transcripts indicating the prerequisite coursework can complete a Data Structures Proficiency Exam to strengthen their application.
Prospective students with this background will then have to complete the University’s application and submit the required fee along with copies of transcripts. Students pursuing Master’s of Computer Science are not required to complete the GRE or submit letters of recommendation, although they can opt to submit letters to enhance an application.
Career Support
The University of Illinois’s reputation is in part supported by the success of its graduates. Indeed, notable alumnae with computer science degrees have founded or led well-known companies such as C3, Malwarebytes, Match.com, Microsoft, Netscape, Optimizely, PayPal, Youtube, and Yelp.
Students also benefit from the University of Illinois’ robust Career Center and Engineering Career Services. This includes a Computer Science External Relations team that manages recruitment efforts and collaborations with corporate partners. The CS-ECE Corporate Connection highlights the ability to facilitate dozens of opportunities for students to connect with prospective employers, thus allowing students to make connections with the companies they want before graduation.
Additional Information
- Program Length: 32 credits
- GRE: Not Required
- Tuition: $21,440
- Program Website
2
University of Wisconsin
The University of Wisconsin (UW) arrived at the second spot in our rankings of data science programs. This Master of Science in Data Science is facilitated through a partnership between UW Extended Campus Office and six campuses. The data science program is well regarded because students are able to learn from the University of Wisconsin’s established faculty and capitalize on UW’s longstanding reputation as a leading institution of higher education. These factors combine with sixth-lowest program cost of the top 15 data science schools in our ratings, and led us to rank the UW Master of Science in Data Science in the second spot.
Course of Study
UW’s Master of Science in Data Science is a fully online program that is grounded in computer science, math and statistics, management and communication. Students must complete 12 specified 3-credit courses in data science, which includes components focusing on statistical methods, analytics, computing and warehousing, data analysis, decision-making and ethics, and a capstone project. The program can be completed in as little as a year. The timeline for program completion, if any, will depend on the home campus each student selects at the time of admission.
Admissions Requirement
Applicants are required to have a bachelor’s degree and a cumulative GPA of 3.0 or higher. In addition, prospective students must have completed prerequisite coursework in elementary statistics, introductory computer programming and introduction to databases, although relevant work experience may be considered in place of this coursework. The application also requires the submission of two letters of recommendation and transcripts. GRE scores are not required. Students can apply to enter the program at the beginning of any term (Spring, Summer or Fall).
Career Support
UW’s Master of Science in Data Science is structured to allow its graduates to enjoy broader career opportunities or implement changes in their existing organizations. This is done in part by relying on an advisory board of industry professionals to ensure classroom learning matches real-life data science. By implementing a well-rounded curriculum that provides graduates with a range of skills in real life settings, UW ensures that students are able to smoothly transition into the workforce after graduation.
Students in the Master of Science in Data Science program complete courses online but receive many of the same benefits of students attending on-campus UW programs. Indeed, credentials such as the degree and transcripts online students receive is identical to that of on-campus students. Also, UW’s large and well-connected career services office, along with other campus resources, are available to support students in the data science programs.
Additional Information
- Program Length: 36 credits
- GRE: Not Required
- Program Website
3
University of California – Los Angeles
The University of California – Los Angeles (UCLA) Online Master in Data Science Engineering landed at the third place in our list. UCLA’s data science program has consistently ranked as one of the top online graduate engineering programs over the past six years. This program cost is slightly higher than the top two schools on our list, but graduates will enjoy a well-respected Master of Science in Engineering with a Certificate of Specialization in Data Science Engineering from a premier university. These factors justified UCLA’s place at number 3 in our rankings.
Course of Study
A minimum of 9 courses are required to complete the 36 credit program and at least 5 of those courses must be at the graduate level. Students have the flexibility to choose 4 core courses in areas such as database systems, analytics, algorithms and Bayesian networks. The remaining courses are electives and UCLA offers students the opportunity to take up to 2 elective courses in areas outside of Data Science Engineering. Students are expected to complete their degrees within two academic years and one quarter, and the maximum time allowed in the program is three academic years. To be eligible for graduation, students must satisfy a comprehensive exam requirement through completion of a capstone project or by passing three graduate level written exams in the student’s area of specialization.
Admissions Requirement
UCLA has a strict graduate admissions policy that specifically requires all applicants to complete a bachelor’s degree in an engineering discipline, computer science, mathematics, chemistry, physics or an equivalent field. In addition, prospective students will need to have maintained a GPA of 3.0 or better during the last two years of undergraduate coursework. GRE scores are generally required, as well as transcripts, three letters of recommendation, a personal history statement, and a statement of purpose detailing the relationship between the chosen area of study and current or future employment goals.
Career Support
UCLA’s Career Center provides support specifically geared toward master’s students. This includes professional development workshops and 1:1 meetings with graduate career advisors. UCLA’s larger career center extends services to students for an additional three months after their last academic term, which helps ensure that graduates receive access to counseling appointments, workshops, career fairs and info sessions that may help connect them to their future employer.
UCLA’s data science program challenges students to be deliberate in identifying a chosen area of study. This begins with each applicant’s creation of a statement of purpose that identifies their career goals. After admission to the master’s program, students build on that statement by crafting a course of study to reach the goals that they defined during the application process. By requiring prospective applicants to identify their career goals first, UCLA increases opportunities to actualize these goals through specialized courses of study.
Additional Information
- Program Length: 36 units
- GRE: Required
- Program Website
4
University of California – Berkeley
Course of Study
The multidisciplinary program at UC-Berkeley is built on computer science, social sciences, statistics, management and law. Students complete a 27-unit program that focuses on skills such as research design, data cleansing, data engineering, data mining and exploring, data visualization, information ethics and privacy, statistical analysis and machine learning. The fully online program can be completed in several flexible paths that allow for completion in as little as 1 year or as long as 32 months. Before graduating, students complete a final capstone project that combines technical, analytical, interpretative and social dimensions into a full data science project. Students are also required to attend at least one 3-4 day immersive in-person experience in which they meet classmates and professors in person, participate in workshops, and network with other professionals.
Admissions Requirement
Prospective applicants must have a working knowledge of fundamental computer science concepts, including data structures, algorithms, and linear algebra. While specific coursework is not required, applications should demonstrate an understanding of these concepts through training, self-study or demonstrated aptitude. In addition, prospective students have the option to document programming experience by showing prior coursework in this area or through a Programming Competency Statement demonstrating knowledge of Python, Java or C++. Applicants are required to have a bachelor’s degree from an accredited university and submit transcripts along with two letters of reference (preferably from a direct supervisor or former employer). While a minimum GPA is not specified, UC-Berkeley highlights that most students have a GPA that is well above 3.0. GRE or GMAT scores are required, except for students that have 8 or more years professional work experience (or a Ph.D. and 5 or more years of professional experience).
Career Support
UC-Berkeley boasts a program that leads to career success in part because of top-notch faculty and students from across the world. The interactive experiences in the online program allow students an opportunity to build close relationships with faculty, classmates and alumni that can be utilized to improve career opportunities. In addition, many faculty actively work in the data science field and, in addition to helping students satisfy course objectives, instructors remain accessible to advise students on how best to reach career goals.
UC-Berkeley also highlights the provision of personalized career support services in the form of 1:1 coaching at every step of the career process. This begins with forming career plans and networking and extends to navigating an offer of employment. UC-Berkely has a strong alumni system as well as career connections with industry leaders and employers that add an additional layer support as students try to find their ideal jobs after graduation. Graduates of the data science program are able to access UC-Berkeley’s larger career office support, which includes elements such as job portals and resume books.
Additional Information
- Program Length: 27 units
- GRE: Required or GMAT
- Program Website
5
University of Maryland
The University of Maryland’s Master of Professional Studies in Survey and Data Science received the number 5 spot in our rankings. The University of Maryland’s data science program is built around award-winning faculty. Graduates benefit of this online master’s program also benefit from the university’s reputation as a premier public research university and land grant institution. The cost of this program is also among the lowest of our top 15 data science programs.
Course of Study
To achieve an online Master’s of Professional Studies in Survey and Data Science from the University of Maryland, students will need to complete 30 credits of coursework. Nineteen credits are accumulated through the completion of core courses in five areas of focus: research question, data generating process, data curation/storage, data analysis, and data output/access. Students are afforded the flexibility to choose among course offerings in these main areas, and are also provided the opportunity to customize their course of study through 11 credits of electives. Most courses are designated as 1 or 2 credits and can be completed in 4 weeks per credit hour.
Admissions Requirement
Prospective applicants must complete the standard University of Maryland graduate application, which requires submission of a statement of purpose and course transcripts. Previous coursework or knowledge in mathematical/applied statistics must be demonstrated through completion of six credits of applied statistical methods courses. Applicants that cannot demonstrate this prior knowledge through their transcripts or work experience will be required to pass an entrance exam. Letters of recommendation and GRE/GMAT scores are not required. In addition, applicants for an online Master of Professional Studies in Survey and Data Science are required to submit resumes or written statements that demonstrate a full year of relevant work experience at the time of application in the areas of survey or census design, data collection or statistical analysis.
Career Support
As with other University of Maryland students, individuals pursuing a Master of Professional Studies online are able to benefit from the services of the university’s larger career office. This includes access to a database of job postings, opportunities for on-campus interviews, assistance with resumes and cover letters, support from career advisors, and informational sessions/workshops. Additional career support specifically designed for graduate students at the University of Maryland is provided through each graduate program, but specific resources for students pursuing their Master of Professional Studies in Survey and Data Science were not identified.
Additional Information
- Program Length: 30 credits
- GRE: Not Required
- Program Website
6
University of Michigan
The University of Michigan’ School of Information features a Master of Applied Data Science that was given the number 6 spot in our ranking of data science programs. This graduate program enjoys the strong reputation that is associated with University of Michigan’s status as a top public University. The faculty and resources provided by the University of Michigan are a strong reason for applicants to consider this program, and the tuition cost is slightly below the median cost of the top 15 data science programs in this ranking.
Course of Study
Students in Michigan’s online Master of Applied Data Science cover topics such as computational methods for big data, exploring and communicating data, methods for visualizing data, analytic techniques, and data science applications. During the program, students will complete three major projects that help build their professional portfolios. The online curriculum is structured in one credit, 4-week course modules that allow the students the flexibility of taking 1-3 credits each month. Students can complete the 34 credit program in as little as 12 months and as long as 3-years.
Admissions Requirement
Prospective students will need to have completed a bachelor’s degree and submit transcripts pertaining to their prior educational experience. Applicants are also required to complete a personal statement and five short essays detailing the reasons they are pursuing a Master of Applied Data Science, personal qualities that will lead them to succeed in the program, a data-oriented problem they have solved, an instance of successfully communicating information to change an outcome, and a reflection of the greatest value and potential harm of data science. Admitted students will also need to pass online assessments in introductory statistics and Python. Three letters of reference are also required, but GRE/GMAT scores are not necessary.
Career Support
The University of Michigan’s program emphasizes practice experience in and outside of classes to provide real-world training. Many students also participate in experiential learning internships. University of Michigan’s iCareers office provides comprehensive career services support that is specifically tailored for students in the information sector. This career support is best reflected in the outcomes of graduates, and 98% of University of Michigan Students from the School of Information report finding employment in their field of choice with 93% reflecting high levels of job satisfaction.
The University also highlights its efforts to work closely in assessing student’s interests, exploring career options, and assisting in the development of effective search strategies. A wide range of resources are offered through the Career Development office to help students from job search to salary negotiation. Prospective students can find proof of this career support by examining the employment reports showing outcomes for recent graduates, which reflect positively on earning levels and employment opportunities.
Additional Information
- Program Length: 34 credits
- GRE: Required
- Program Website
7
Johns Hopkins University
Johns Hopkins University (JHU) offers a Master’s of Science in Data Science program that can be completed fully online or through hybrid online/on-site opportunities. This program’s reputation is enhanced by student’s ability to learn from practicing engineers and data sciences while accessing state of the art facilities at Johns Hopkins Applied Physics Laboratory. As a result, JHU graduates enter the career field with a degree from a well respected institution that will increase career opportunities.
Course of Study
JHU’s curriculum for the Master of Science in Data Science program focuses on the fundamentals of computer science, statistics and applied mathematics and incorporates learning from real-life scenarios. Students begin with foundation courses in algorithms, statistical methods and data science, and build on these with required courses in advanced data science, visualization and statistical models and regression. JHU’s data science program allows students the flexibility to select among multiple options for required courses, as well as an array of electives that allow students to develop more specialized knowledge in particular areas. To complete the program, students are expected to have the skills to balance theory and practice of applied mathematics and computer science to analyze large scale data sets, discover relationships and insights into data sets, and create models and formal abstraction techniques to solve real life problems. Ten courses must be completed within a 5-year period and students must earn better than a ‘C’ for 9 of those courses.
Admissions Requirement
Prospective applicants must have earned a bachelor’s degree and maintained a GPA of 3.0 or better for the latter half of their academic studies. The application process includes submission of a transcript and GRE scores are encouraged but not required. JHU also specifies that applicants must have completed a number of prerequisite courses with a grade of B- or better: (1) multivariate calculus; (2) discrete mathematics (although linear algebra or differential equations can be substituted); (3) courses in Java or C++; and (4) a course in data structures. In addition, students are expected to be competent in Java programming, although competency in Python can be accepted on a case-by-case basis. Prospective students may be provisionally admitted without this coursework, but students must complete these prerequisites before commencing required courses.
Career Support
The JHU Career Center facilitates career fairs, information sessions and staff presentations that help students find the right career. The Career Center includes a career planning website, as well as career webinars taught by JHU experts that address issues online and part-time graduate students may encounter in industry. Networking with current students and alumni is also facilitated through the Career Center and this can help program participants find vital connections to locate the jobs they want after graduation.
Additional Information
- Program Length: 30 credits
- GRE: Not Required
- Program Website
8
City University of New York School of Professional Studies
The City University of New York (CUNY) School of Professional Studies offers an online Master of Science in Data Science that lands within our top ten data science programs. CUNY created a strong reputation by building its program around established faculty and practitioners combined with partners in industry and education. CUNY’s Master of Science in Data Science achieved a ranking in our top-10 data science schools by combining this quality education and reputation with tuition costs that were lower than most comparable programs.
Course of Study
CUNY’s Master of Science in Data Science is a fully online degree program that challenges students to build portfolios of increasing complexity that parallel today’s IT demands. Students work through prescriptive and predictive models, design and practice presentations, and review the work of classmates. CUNY designs the program curriculum around current employer needs, and graduates are required to complete a capstone project that focuses on creating a practice solution to a real world problem. The specific program learning outcomes focus on five areas: (1) data acquisition, management and programming; (2) foundational math and statistics; (3) modeling; (4) model implementation and deployment; and (5) dissemination. The 30 credit program is composed of 21 required credits and 9 elective credits (3 courses).
Admissions Requirement
Prospective applicants must hold a bachelor’s degree from an accredited institution and demonstrate a cumulative GPA of 3.0 or higher. The application process includes submission of a personal statement, resume and two letters of recommendation. GRE/GMAT scores are not required. While students from diverse fields are welcomed, current skills in areas such as statistics and probability, linear algebra, programming, relational databases, and analytical thinking must be demonstrated. These skills can be shown through completion of credit bearing coursework with grades of B or better in these subjects, two or more years of relevant work experience developing such skills, or by satisfying a challenge exam that is designed to assess knowledge in these areas.
Career Support
CUNY’s Master of Science in Data Science is designed to prepare graduates for technical and managerial positions, such as data scientist, business intelligence analyst, knowledge and informatics engineer, data analyst, data mining engineer, and data warehousing manager. CUNY’s Career Services supports graduates with a wide range of services to assist all students in preparing resumes and cover letters and searching for employment. CUNY highlights that graduates leave with project-based samples of their work that are similar to that of programming bootcamps.
Additional Information
- Program Length: 30 credits
- GRE: Not Required
- Program Website
9
University of Houston
University of Houston’s Master of Science in Statistics and Data Science is a hybrid program combining on-campus and online courses. This program began in Fall 2017 and has quickly been building a reputation by mentoring students with top professionals that have years of experience in teaching in research. The University of Houston has achieved this name recognition while remaining one of the lower cost options in our listing of the top 15 data science programs. This balance of cost effective professional training led to the University of Houston’s inclusion in our top 10 rankings.
Course of Study
The University of Houston’s program requires the satisfactory completion of 30 credit hours. Full time students can graduate in one calendar year if full time while part-time students have 2 years. The bulk of the program is comprised of 8 core classes: probability models and statistical computing, linear models and design of experiments, statistical learning and data mining, programming foundation for data analytics, applied statistics and multivariate analysis, deep learning and artificial neural networks, data visualization and big data analytics. Students also select 2 elective courses and complete a 3 credit summer internship project to round out their studies.
Admissions Requirement
Applicants are required to hold a bachelor’s degree with a GPA of 3.0 or higher over the student’s last 60 credit hours. Prospective students will need to submit GRE scores, transcripts detailing prior coursework, three letters of reference, a resume and personal statement. While a background in probability, statistics, or proficiency in a main programming language are not specifically required, these factors will enhance an application and are helpful. Students are required to have completed prerequisite courses in Call II and Linear Algebra before commencing studies.
Career Support
The University of Houston’s Master of Science in Data Science program facilitates career opportunities through student’s participation in project-based internships in research, industrial, commercial or biomedical settings. These internships were a unique element of this program’s hybrid training and provided a level of real-life practical experience that provided graduates with a career edge. Participants in the master’s program also are able to access the panoply of services provided by the university’s larger career services office. In addition to the resume services, search tips, and job lists provided by the broader career services office, the University of Houston facilities some specific career support for data science students. This included a list of career and event opportunities with potential employers in data science.
Additional Information
- Program Length: 30 credits
- GRE: Required
- Program Website
10
Colorado State University
The Colorado State University (CSU) Master of Applied Statistics with a Data Science Specialization landed in the number 10 spot in our rankings list. This program came at the second lowest tuition cost of our top 15 data science programs. CSU has been building its reputation through faculty that keep students up-to-date by incorporating active research projects into the curriculum. Students in the CSU data science program are able to use a quality master’s degree from CSU to move into a data science career at a cost lower than many other programs.
Course of Study
Students in CSU’s program focus on applied statistical procedures, analytics, data visualization, and statistical computing. Thirty-one credits are required for graduation. The course of study includes 13 required courses that compose 23 required credits, and 5 elective courses. The foundational coursework includes linear models and methods, statistics and probability. More advanced classes focus on a variety of statistical models and methods such as spatial statistics, Bayesian modeling, time series analysis and visualizing data. A final capstone project challenges students to bring skills learned in the classroom into a real life workplace.
CSU’s program utilizes a 8-week subterm structure that culminates in a 6 week capstone course. This allows full-time students the ability to graduate in less than a year or part-time students can work on their degrees for as long as 4 years.
Admissions Requirement
To be eligible, prospective applicants must have a 4-year bachelor’s degree from an accredited university, 3 semesters of calculus, 1 course in linear algebra, and at least 1 course in statistics. Before beginning official coursework in the program, admitted students are required to complete two noncredit classes focused on math and computing skills for statistical analysis. The application process requires the submission of three letters of recommendation, a resume, personal statement outlining professional and educational goals, and math entrance exam or GRE scores. CSU did not specify a particular major that is required or a minimum GPA.
Career Support
CSU designated a specific Student Success Coach to assist students in the Master of Applied Science program. Students are additionally able to access the larger CSD Career Center, which assists students in guiding career searches, improving job search materials, and locating satisfactory employment. CSU also created a specific guide that was created with partners in industry and experienced staff to assist its master’s students pursuing jobs in industry.
Additional Information
- Program Length: 31 credits
- GRE: Required
- Program Website
11
Northwestern University
Northwestern University’s (NU) Online Master’s in Data Science is built on strong name recognition. NU’s program has been around longer than several of the other programs identified in our top-15 ranking and has built a steady reputation during its history. The tuition cost associated is among the higher of the programs listed in our rankings. This balance of a long-standing positive reputation with higher tuition costs led to NU’s placement at 11 in our rankings list.
Course of Study
Students in Northwestern University’s program can pursue a general data science track or a specialization in Analytics and Modeling, Artificial Intelligence, Data Engineering, or Analytics Management. Students are required to successfully complete 12 courses, which includes 6 foundation courses, 1 course in leadership or project management, 2 courses in a specialization, and 2 electives. All students also complete a capstone project or thesis.
The Analytics and Modeling Specialization focuses on preparing students to utilize algorithms for predictive modeling and analytics and to develop programs that can be applied to business applications, such as marketing and finance. The Analytics Management Specialization helps students develop communication and management strategies for data-driven leaders. The Artificial Intelligence Specialization teaches students contemporary data-adaptive models employing machine learning and how to use solutions in computer vision, natural language processing, and software robotics. The Data Engineering Specialization builds skills related to understanding computer systems and solving problems regarding data security, organization and collection. NU also offers a General Data Science Track that can be selected instead of a specialization for students that anticipate performing a range of data science functions in an organization.
Admissions Requirement
To be eligible for admissions, prospective applicants must have a 4-year degree. NU does not specify a minimum GPA or required background skills. The admissions process requires submission of a resume, statement of purpose, transcripts, and the contact information for two references. GRE/GMAT scores are not required.
Career Support
Northwestern University provides career advising to students through academic advisors and larger career support through the NU Career Advancement office. This office provides advising, programming and resources to all Northwestern University students and is accessible for six months following graduation.The Career Advancement office facilitates a wide variety of programs, such as mentoring and externship opportunities, and career fairs. This office also maintains job and alumni networking databases.
Additional Information
- Program Length: 12 courses
- GRE: Not Required
- Program Website
12
Rutgers University
Rutgers University’s Master of Business and Science Degree landed at the 12 spot in our rankings list. Rutgers program allows students to pursue an online Master of Business and Science with a Concentration in Analytics that is associated with Rutgers University’s well-respected business school. The program is offered both in a traditional on-campus setting and through a hybrid option that combines online classes with 1 week a year spent on campus. Rutgers University’s program has earned a well-deserved reputation of its graduates finding analytics jobs in top companies. This comes at a tuition cost that was second highest of our top 15 schools.
Course of Study
Rutgers University Master’s of Business and Science Degree is split between business and science courses while still allowing students the flexibility to adjust their coursework to their personal interests and business goals. The curriculum pairs business topics like accounting, finance and market assessment with data science subjects such as data warehousing and regression analysis. Students have the ability to take a wide variety of electives in topics including advanced statistics, business intelligence, advanced computing and bio-informatics. Additionally, data science workshops in topics such as R, SAS, Stata, Python, etc. are offered every semester and allow students a number of opportunities to devote extra time to enhance their technical skills. To be eligible for graduation, students will need to complete 24 credits of science courses, 19 credits in business courses and attend 12 colloquium events.
Admissions Requirement
The data science program is designed for students that have a background in Engineering, Analytics, Computer Science, Mathematics, Statistics and related disciplines. Prospective applicants will need to demonstrate a cumulative GPA of at least 3.0 and submit GRE scores. Students will also need to have completed 1 year of calculus and courses in undergraduate programming and statistics, but these can be taken during the master’s program and will count toward the degree.
Career Support
Rutgers University highlights that its campus is geographically located near the larger metro-New York City area and many of the desirable analytics jobs sought by its graduates. The program curriculum is informed by labor analysis of the skills required by employers in industry and this ensures that each course of study is carefully informed by the actual skills graduates will need to compete in the data science labor market. These steps enhance the practical training provided to students in the master’s program and provide a subtle layer of career support. Rutgers highlights that its students have positive outcomes after completing the program, with a 96% employment rate within 6 months of graduation.
The master’s program also includes career coaching and networking opportunities, including a full time career specialist assigned to Master of Business Science students and access to an executive coach. Some of the practical career support offered to program participants is structured into the learning program. For example, Rutgers’ externship exchange program allows for a unique opportunity for students to gain experience by participating in real world projects in the business, nonprofit and/or government sectors. Students in the online Master of Business and Science program can also access the range of career support provided by the larger Rutgers University, including resume review, career services and workshops.
Additional Information
- Program Length: 43 credit hours
- GRE: Can be waived
- Program Website
13
University of California – Riverside
The University of California at Riverside’s (UC-Riverside) Master of Science in Engineering in Data Science landed at the 13th spot in our ranking list. UC-Riverside’s program was born out of the larger University’s well-respected Bourns College of Engineering. The Master of Science in Engineering in Data Science blends engineering skills with management strategy and has produced leaders in the field of data science. This track history and engineering reputation combined with a program cost that is less than many comparable programs justified its inclusion in our ranking of top-15 data science master’s programs.
Course of Study
This 36-credit program allows students an opportunity to graduate in as little as 13 months. UC-Riverside’s program is focused on assisting students with the development of techniques to identify, analyze and visualize hidden patterns in data groups. The curriculum consists of 16 credits (4 courses) of core engineering classes that is complemented by 16 credits (4 courses) of electives that students use to build a specialization. The data science specialization is one of six offered to participants in the Master’s of Science in Engineering program. Completing the program requires participation in a 4-credit capstone course.
Admissions Requirement
UC-Riverside’s data science program is geared to students with engineering experience or a bachelor’s degree in Engineering. Students with bachelor’s degrees in related fields can also be considered. The application process requires submitting transcripts, letters of reference, and GRE/FE scores. While a minimum GPA is not specified, past academic performance, along with professional experience and certifications, is considered in evaluating applicants.
Career Support
Students at UC-Riverside’s data science program can access the larger university Career Center. This office offers a range of services to assist in all of the steps associated with searching and applying for jobs, and facilitates career fairs that can help students connect with jobs. The Career Center offers some specialized services geared at UC graduate students, including a graduate student liaison.
Additional Information
- Program Length: 36 credits
- GRE: Required
- Program Website
14
Indiana University – Bloomington
Indiana University – Bloomington offers an online Master of Science in Data Science program that landed in our ranking of the top 15 data science programs. This program was designed for working professionals from diverse backgrounds and mirrors Indiana University’s on-campus Master’s of Science program. Indiana University has developed a reputation as a quality program at a cost that is slightly higher than that of the other master’s programs included in this ranking.
Course of Study
Indiana University’s program is offered in a fully online format but students have the opportunity to participate in an optional Online Immersion Weekend’s each spring. These events create opportunities for students to gain hands-on experience with new data sets and provide participants with the opportunity to engage in face-to-face meetings with experts in the field. Completing Indiana University’s program requires accumulating 30-graduate level credits. Six credits are in core areas, 15 credits are elective courses, 6 credits are in domain specific areas, and 3 credits are fulfilled through each student’s capstone project. Students focus their studies in one of four domains: data analytics and visualization, intelligent systems engineering, precision health or cybersecurity.
Admissions Requirement
Indiana University requires that all applicants hold a 4-year bachelor’s degree but does not require that students hold specific majors. Nonetheless, prospective students are advised to possess knowledge of mathematical and statistical principles, such as linear algebra, calculation and probability. Students are also expected to have familiarity with the basic concepts of object-oriented programming, experience with data structures and algorithms, and a basic understanding of both Python and R programming languages. Indiana University does offer a Data Science Essentials online coursework packet to help students that do not already have this background build the requisite skills.
The application process includes submitting a resume, personal statement, 3 letters of recommendation and transcripts. Students in the online program do not need to submit GRE scores.
Career Support
Students at Indiana University’s Master of Science in Data Science receive varying forms of career support. As part of the master’s program, the Online Immersion Weekends allow students the ability to facilitate face-to-face connections with current professionals before job searches begin. Indiana University also has other specific career support for data science students, including internships, research projects, hackathons, and an annual bootcamp. The larger University’s career support center also provides more generalized career support, including resume and application tips as well as the Luddy Careers portal to search and apply for jobs and locate employer-related events.
Additional Information
- Program Length: 30 credits
- GRE: Required
- Program Website
15
University of Southern California
The University of Southern California (USC) Viterbi Master of Science in Applied Data Science earned a spot in our rankings of the top 15 data science programs. USC’s Viterbi School of Engineering is considered among the best engineering programs in the world and provides an exceptional name value for graduates of the Master of Science in Applied Data Science Program. Degrees from this prestigious private university also come at a higher cost, and USC’s Master of Science in Applied Data Science had the highest tuition cost of the programs included in our ranking of the top 15 programs.
Course of Study
Students that do not already have a strong background in computer science will begin by learning data science basics, such as data formats, tools and techniques, as well as building data processing programs and applying analytical tools. More advanced data science courses will focus on topics such as data management, machine learning, data mining and statistics. Students also have the option to select a number of elective courses, which will depend on how many basic courses they needed to begin the program. The program culminates in a professional practicum that involves working in teams on external customer data analytic challenges. This provides students with an opportunity to use real client data and develop solutions that can be delivered to actual stakeholders. To graduate, students must complete 32 units and achieve a cumulative GPA of at least 3.0. Online students must complete their degrees in a 3-year period.
Admissions Requirement
Students from a range of backgrounds that have completed a 4-year bachelor’s degree are eligible but all students are required to have a strong math and science background. A minimum GPA is not specified, but candidates are cautioned to show strong academic records, specifically in engineering and related courses. GRE scores are required, along with letters of recommendation and a statement of purpose.
Career Support
Students in USC’s Master’s of Science in Applied Data Science program receive support from Viterbi Career Connections. This office provides support to students in the Viterbi School, including advising sessions, workshops, events, and assistance with building career tool kits. Graduates also benefit from USC’s impressive alumni network. One element of career support is built through the program’s professional practicum experience, which allows for real world experience that can be used to increase networking and helps make graduates of USC’s program attractive to future employers.
Additional Information
- Program Length: 32 units
- GRE: Required
- Program Website

6 Steps to Choosing an Online Data Science Master’s Program

Step 1: Determine your data science specialty

With such a large number of schools offering online data science programs, students have a wide variety of choices.

What are your career goals? Which concentrations increase the number of career opportunities?

There is considerable overlap among the core courses. Data mining, data warehousing, data analytics, and statistical modeling are the essential courses that are common within all programs.

However, due to the differing needs of each market sector, e.g., law enforcement, finance, healthcare, etc., universities now include an array of elective courses and specializations. For example, Social Media Analytics, Game Theory, Cryptology, Cybersecurity, and Financial Investigations can be targeted areas of study for the aspiring data scientist.

Step 2: Determine your timeline

The timeline for both starting and completing a master’s in data science online degree program can vary by school.

What are the application deadlines? Are you planning to attend full time or part time? Is the program synchronous or asynchronous?

Step 3: Research how long each program has been offered

While online data science degrees are relatively new, the programs that have been around the longest tend to be the better choice.

Online data science master’s degrees that are accredited, have excellent student support, and job placement should be at the top of the list in terms of what constitutes a good program. We’ll dive into each of these further below.

Step 4: Determine standardized testing requirements for admission

Roughly half of the schools listed require GRE scores. For those of you who excel at scoring highly on standardized tests, this may not be a factor that impacts your decision to apply. However, for prospective students who haven’t taken the exam or did not score well, there are plenty of schools where the GRE is not required as part of the application process.

Step 5: Determine the cost

Cost is usually the top consideration for most students

Schools do not publish their tuition information in a standardized format. For example, school A may list the cost per credit at $1,000 and school B may list the cost per course of $3,000. If both schools offer three-credit courses, the cost is identical, but school B may appear more expensive at first glance.

We do our best to keep tuition rates below listed as accurately as possible. However, many schools adjust their rates on a yearly basis. As such, it is best to confirm current rates directly with schools once you have narrowed down your options.

Step 6: Choose a school

Once you have researched all of these factors (and potentially others), it is time to make a choice. The good news is there are many prestigious schools offering a data science master’s online, so there are plenty of options.

How Long Does it Take to Get an Online Master’s in Data Science?

On average, master’s degree programs can be completed from anywhere between 18 months to 36 months.

Longer doesn’t necessarily equate to a better program. It’s the quality of the education that is the most important.

As previously mentioned, the core coursework is virtually identical from program to program. However, many universities have math and programming knowledge requirements that you’ll need to fulfill prior to admission. On the other hand, there are online data science master’s degrees that will offer this type of coursework, e.g., calculus, statistics, and a programming language, as the first set of courses you’ll complete. Naturally, this will extend the length of your program.

While asynchronous vs. synchronous programs don’t automatically translate into a longer vs. shorter program, you should certainly choose a learning delivery method that matches your preferred learning style. In short, asynchronous courses involve pre-recorded lectures that you can watch at your leisure. There are, of course, due dates for assignments such as contributing to discussion boards, turning in required assignments, and completing exams. Synchronous learning modules incorporate live lectures along with asynchronous discussion posts, assignments, and tests. Alternatively, some programs may require live proctored exams and students can schedule real-time virtual assistance with their assignments (some have Telegram groups for this purpose as well).

Signs of a Strong Data Science Program

In the U.S., the higher education accreditation system, in conjunction with the U.S. Department of Education (ED) and the Council for Higher Education Accreditation (CHEA), ensures that colleges and universities have a verified and high-quality level of academics. Although each region of the U.S. has its own accreditation agency, ED and CHEA oversee the accreditor recognition process.

Secondary schools are not required to be accredited at any level. However, those schools who do not become nationally accredited will not be able to offer Federal Student Loans. Some employers will not look highly upon a degree that’s earned from a non-accredited school. Thus, it would be to your most significant benefit to attend an accredited school.

Student support and resources are also essential aspects of finding the right program. These frequently include student outreach, tutoring, assistance with applying for financial aid, and access to the online library for research. On campus resources tend to be more expansive: mental and medical health clinics, campus police, and computer centers.

Job placement can also be considered a part of the student support and resources made available to both on campus and online students. Since data science is one of the most in-demand careers, and employer demand is currently outpacing the supply of well trained and experienced data scientists, many schools have job placement agreement with employers. We’ve created a data science job guide that will provide additional information for your data science job search.

Admission Criteria and Curriculum

The admission criteria is relatively standardized between schools.

You’ll be expected to have earned a bachelor’s degree from an accredited institution. Most, if not all, universities have a minimum GPA, usually the lowest being a 3.0 average for all undergraduate coursework. Every institution requires official transcripts for each post-secondary school you’ve attended.

Additionally, be prepared to gather recommendations and to write a personal essay or statement of purpose consisting of 500 words.

Since educational content is delivered in English, international students may need to send TOEFL or IELTS scores as verification of English fluency.

The main coursework you’ll encounter throughout all of the data science master’s degree programs includes statistics, one or more programming languages (e.g., R, Python), machine learning, data visualization, business analytics, and big data. Business analytics and big data may seem to be the vaguest titles.

Mainly, in business analytics, you’ll be learning to use one of the widely used analytics systems such as Microsoft Power BI or IBM Cognos Analytics. Along with additional software knowledge, you’ll gain an understanding and application of how data science, business logic, and businesses processes are intertwined.

Big data courses will teach you the essentials of working in a cloud-based environment which includes the basics of data storage, data warehousing, and ETL (extract, transform and load) processes. Google Cloud Platform, Amazon Web Services, Cloudera, and Hortonworks (Hadoop) are a few examples of the big data platforms you may be required to learn during the program.

Top Careers for Graduates with a Master’s in Data Science

Every industry has a need for data scientists.

The choice as to which specific career trajectory is dependent on both your interest as well as where you have the most expertise. Marketing departments, universities, governments, startups, tech giants, the pharmaceutical industry, and the world of finance are perpetually seeking qualified data science candidates.

For a closer look at some of the industries leveraging the power of data science, you can take a look at our data science industries page.

Alternatively, given the advanced analytical skill set that data science master’s degrees provide, you can choose to become a:

Data scientist (Median salary: $100,910 )
Statistician (Median salary: $95,570)
Database architect (Median salary: $123,430)
Computer and information research scientist (Median salary: $131,490)
Software developer (Median salary: $120,730)
Operations research analyst (Median salary: $82,360)

Along with these roles, people with Master’s degrees in data science often become data experts in healthcare, finance, insurance, and any industry that runs on vast sets of data.

The location of the job, as well as the size of the enterprise, may dictate which end of the pay scale you’ll likely earn. For example, the Bureau of Labor Statistics (BLS) reports that data science professionals in the San Jose area have a median salary of $157,110 — a higher mean salary compared to national statistics.

If upward career mobility is important to you, and you begin interviewing for data science positions, do not be hesitant to ask about promotional opportunities within the company (particularly if or when the employer asks if you have additional questions). Is the potential for promotion available? If so, what are the criteria to be considered for advancement?

Pros and Cons of Online vs. Campus-Based Master’s Degrees

Convenience is the main pro of online data science master’s degrees. There’s no need to take the time needed to drive to campus, find a parking place, and make your way to a classroom. For busy professionals who have a full-time job and/or family responsibilities, online degree programs are enormous time savers. The cost may or may not be equitable as campus-based degrees tend to incorporate a technology fee into their total tuition calculation.

One of the downsides of online degree programs is decreased access to the professor. When you’re sitting in a classroom, you’re usually able to immediately ask questions during the lecture or seminar. Furthermore, when you’re working on an in-class assignment, the professor is present to help you through a challenging task. Many online programs where the professor is live streaming the lesson often provide real-time chat capabilities. However, for completing assignments you’re either entirely on your own (along with resources such as eBooks and possibly transcripts of the lecture), or you’ll need to engage in a delayed question and answer session through discussion boards and email.

Both on-campus and online data science degree programs require self-regulated time management. It’s easy to fall behind in the coursework if you are not dedicating time to attend the real-time classes and complete the assignments. Six to eight hours per week is generally the minimum amount of time you’ll need to set aside for class time (or live streaming lecture), assignments, and exams. This is where online programs have an additional upside: rather than spending the time driving to and from campus, all you’ll need is a laptop or desktop and a comfortable work environment. There’s a bit of a caveat, however. You’ll need a reliable computer system that can handle a moderate to large memory load and computational speed for both the live streaming lectures and the various data science software requirements.

FAQs

Do I need a Master’s in Data Science to pursue a data science career?
Generally speaking, yes. Without a master’s degree, it’s quite difficult to demonstrate to prospective employers that you have the skill set and breadth of knowledge needed to perform expert-quality work on their team. While there are associate’s and bachelor’s programs in data science, these generally give students the core competencies needed to gain entry level work experience or simply to attend a graduate program – they do not, however, prepare students for the full demands of a data scientist’s duties. If you’re serious about starting a lucrative career as a data scientist, it is highly recommended to pursue your master’s degree.

Does a data science degree make one eligible for any big data job?
No. Any advanced degree in data science involves a concentration that will give you an area of specialization, leading directly to a particular career path. Confusingly, “data science” is often the general name for a master’s degree in any field of big data, but data scientists themselves perform specific roles in companies that differ from, say, data analysts or cybersecurity experts. Data scientists are the team members who sort through and evaluate raw data to figure out what operations-related questions it might answer. These questions are then given over to data analysts to actually apply them to collected datasets and in turn, present them to company leadership. To learn more about the difference between a data scientist and a data analyst, take a look at our guide here.

If a Master’s in Data Science is the industry standard, why do working data scientists pursue additional certification?
While certification programs are not recommended for those who don’t hold master’s degrees, they are a great option for working professionals who would like to expand their knowledge on a particular aspect of data science or refine a specific skill that will make them eligible for more specialized work. These programs can also be excellent opportunities for data scientists who have been working in the field for a long time to learn about new technologies and techniques in a rapidly changing field. However, unlike master’s degrees, data science certifications are not required by employers; rather, they confer expertise beyond what is expected.

School Listings

Bay Path University – Longmeadow, Massachusetts
MS in Applied Data Science

The Master’s program has two tracks, generalist or specialist, to cater to students with different background (STEM, business or social sciences) and interests. Both tracks have comprehensive coverage in statistical and machine learning methods.

Each track consists the core of 3 statistics courses, 2 data mining/machine learning courses, data visualization, database systems, capstone and 3 electives in including text mining, time series, deep learning and other management courses. Focus is in business application, with heavy emphasis in R, Python, SAS and SQL programming skills.

Program Length: 36 credits
Delivery Method: Online
GRE: Not Required
2022-2023 Tuition: $19,235 total

Additional Programs

Other Degrees and Certificate Programs

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Online Data Science Master’s – Guide to Choosing a Program

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School Rankings

Top 15 Ranked Online Master’s in Data Science Programs

1

University of Illinois at Urbana-Champaign – Champaign Illinois

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2

University of Wisconsin

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3

University of California – Los Angeles

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4

University of California – Berkeley

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5

University of Maryland

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6

University of Michigan

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7

Johns Hopkins University

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8

City University of New York School of Professional Studies

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9

University of Houston

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10

Colorado State University

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11

Northwestern University

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