A master’s degree in data science helps prepare professionals to take the next career step. Since data science combines a few fields, like statistics and software development or engineering, a master’s degree program offers a background in the latest skills and technologies.
Over the past few decades, more and more companies, nonprofit organizations, and governmental agencies have grown increasingly dependent on the ability to collect, organize, analyze, and interpret data to make informed decisions. Constant upgrades in data management systems, data analytics software, and data mining have made it easier to perform these tasks on a more consistent and reliable basis.
With the new need for better data, professionals schooled in the ability to evaluate data and create presentations and reports to summarize their findings to help with decision-making processes are needed in nearly all industries.
Jobs in data science, data analytics, business intelligence, statistics, and computer information systems have continued to grow in popularity and demand. As such, relevant degree programs in these areas have also increased, with many colleges and universities offering bachelor’s and master’s degree programs in these and similar areas of study.
This article will focus primarily on data science, a graduate degree in this field, and a data scientist or data analyst career. With many employers preferring a master’s degree in data science for those seeking to fill roles as data scientists or analysts, we will discuss the data science master’s degree in detail. We’ll describe what it is, the online availability of such a degree program, what careers one could expect to pursue after earning this graduate degree, and other pertinent information regarding this degree and career options.
What is a Data Science Master’s Degree?
A data science master’s degree program, which typically results in being awarded the master of science degree, offers advanced studies in such subjects as data modeling, data visualization, applied statistics, data mining, and research methodologies.
Other courses likely to be taken in a data science master’s degree program curriculum include computer science, software engineering, database systems, and machine learning.
Students can usually opt to complete a master of science in data science, master of science in applied data science, or master of applied data science program on a full- or part-time basis. In some cases, the part-time option is best for professionals working in the field who are pursuing a master’s degree for career advancement purposes and cannot necessarily take on a full-time course load. In these cases, students might take as little as two courses per semester.
Some master’s degree programs in data science offer areas of specialization; these specializations can include:
- Artificial intelligence
- Analytics and modeling
- Data engineering
- Analytics management
- Business analytics
- Business intelligence
- Data mining
- Data warehousing
Online Data Science Master’s Degree Programs
As of 2021, more than 30 universities offer online master’s degree programs in data science. Many programs are 100 percent online; others combine online with in-class studies.
Online studies offer the flexibility that would be attractive to professionals adhering to a full-time schedule and find attending on-campus classes challenging. Online studies often allow students to study independently, so professionals can fit classes into their schedules and meet other obligations.
Courses common to online data science master’s degree programs include:
- Big data
- Data analytics
- Machine learning
- Statistical analysis
- Database management
- Predictive analytics
- Data warehousing
- Business data analytics
Data Science Master’s Program Tuition
How affordable is a data science master’s degree?
Several factors would impact the cost of obtaining a master’s degree in data science. The cost of a fully online program would differ from that of an on-campus program; tuition for an in-state student would likely be less than that of an out-of-state student; commuting students would pay less than those living on-campus and paying for college housing.
Per-credit costs will also vary from one school to another. As an example: Southern Methodist University, which offers an online Master of Science in Data Science, charges $1,704 per credit for this program for the 2020-2021 academic year, while the per credit cost for Indiana residents to take the online MS in data science program at Indiana University is $478.82 (non-residents: $782.71 per credit) in 2021.
Some schools might charge flat rates for an entire program; others, such as the University of Texas at Austin, charges per course ($1,000 per course for its online master of science in data science program).
In addition to financial aid in the form of student loans and grants, students could apply for scholarships to help offset the costs of a master’s degree program in data science.
Many colleges and universities offering a master’s degree in data science offer school-based scholarships. There are many businesses and organizations that offer scholarships to students pursuing a STEM degree who meet specific academic and other requirements, regardless of what university they are attending. Qualifications for applying for a scholarship could include academic standing, gender, ethnicity, proof of financial need, and even the intention of pursuing a doctorate in the field.
Most online and on-campus master’s degree programs in data science contain between 30–36 credits and can be completed in two years; some can be completed in less time, as little as 15 or 21 months.
Many master’s degree programs in data science are course-based only; some will involve completing integrative projects or culminating practicums that require students to demonstrate their understanding of concepts studied throughout the coursework. In some programs, projects are reviewed by industry professionals and instructors.
Some programs will offer internship opportunities allowing for the practical application of methods and techniques in professional settings. Students might complete on-campus internships working on collaborative projects with faculty and other students or off-campus internships with businesses or organizations. In many cases, an internship is optional and is listed along with other electives. Some internships are offered only during the summer.
Students can choose between completing a project or entering an internship in some programs.
Master’s in Data Science Career Track
So, once a master’s degree in data science has been earned—either online or on-campus or through a combination of both—what can you do with it?
Many who earn this degree go on to become data scientists. Other possible career titles for those holding a Master of Science in data science include data analyst, business intelligence analyst, data architect, data engineer, database administrator, or systems analyst.
Some could choose to apply their understanding of data analytics gained through their studies to focus on a single area of business; examples would include a marketing analyst, operations analyst, or sales analyst. In these roles, professionals would gather and evaluate data to help make decisions in marketing campaign development, business planning strategies, production growth, or pricing strategies.
More recent and growing job opportunities in the field of data science are those listed below:
- Enterprise architect: these individuals assess business technologies and suggest those best suited to align with a specific organization’s goals and visions
- Machine learning engineers: in this role, professionals develop solutions-based applications using a deep knowledge of various programming languages, interfaces, and algorithms
- Business intelligence developer: BI developers customize analytic software and applications to help business leaders make quicker and more informed decisions in various areas of operations
- Analytics translator: coordinating complex analytics processes to arrive at business solutions, managing analytics projects, and solving problems using applied intelligence and data storytelling techniques are the primary responsibilities of professionals filling this role.
Data Scientist Salary
According to May 2020 information from the U.S. Bureau of Labor Statistics (BLS), data scientists earn a median annual wage of just over $98,000. While the BLS does not supply job outlook statistics directly focusing on data scientists, it does predict a 15 percent job growth rate over the 2019-2029 decade for computer and information scientists who, according to the BLS, perform many of the tasks of a data scientist, such as collecting data and helping businesses analyze this data for decision-making purposes.
Data Science Master’s FAQs
While the information provided is intended to cover the usual details one might look for when it comes to data science master’s degree programs and careers, some questions may not have been addressed. This section includes questions that you might be wondering about if you are considering an educational and professional pursuit in this field.
Yes, the MS in data science is typically classified as a STEM program.
Typical prerequisites include mathematics, statistics, probability, and computer programming courses. Other suggested prerequisite courses include linear algebra, calculus, and computer science.
Some schools will require that students who have not taken some prerequisite courses take placement exams to determine if they need to complete introductory coursework as part of their master’s degree program requirements.
In most cases, a bachelor’s degree in relevant areas such as technology, science, math, or engineering is necessary. Some programs require a minimum undergraduate grade point average.
Some schools will waive the GRE/GMAT requirements for applicants with a specific number of years of experience in the data analysis field.
Some MS in data science programs are hybrid programs, which require students to attend campus to work with an instructor on a required project or complete an on-campus internship.
In many cases, courses build on one another, also known as integrative, so data science courses are often taken sequentially.