Data science is still hot. Yes, the applicant pool for each data scientist job listing is growing. Yes, it’s been almost a decade since the Harvard Business Review called data science the sexiest job of the 21st century. Granted, data science is no longer “the next big thing.” It is still big, however.
A lot has changed since the turn of the millennium. Among those changes: a big increase in the number of graduate programs dedicated to data science degrees. That’s a big part of why there are now so many more data scientists than there were even two years ago, when LinkedIn reported there were over 150,000 more data science jobs than there were qualified professionals to fill them. Competition for open positions is a lot fiercer than it once was.
What can that tell us about whether data science master’s degrees are worth it? Not enough, actually, because programs vary significantly from school to school. There are rigorous Master of Science in Data Science programs at top computer science schools. There are also data analytics degree programs billed as data science programs at plenty of unranked colleges and universities. It can be hard to tell them apart without a deep dive.
What we can conclude from the glut of data scientists is that if you want to work in this field, you’re going to need a master’s degree—full stop. Working your way into data science from analytics after completing a boot camp or a MOOC sequence won’t cut it in a job market where even smaller companies can afford to be more selective about whom they hire. Graduating from one of the top data science master’s programs can potentially give you a huge advantage in your job search.
In this article about the best data science master’s programs, we cover:
Dedicated data science master’s degree programs are for students who already have some experience in analytics and advanced technology or a background in IT, computer science, engineering, mathematics, or technology. They want to dive deeper into the applications of analytics. They also hope to gain industry experience and contacts that will help them land higher-paying data science positions. They’re passionate about finding new ways to leverage the vast quantities of untapped data collected across industries. In some cases, they aspire to transition into higher-ranking management and executive positions like Chief Data Officer or Chief Technology Officer.
According to the University of Virginia (Main Campus)’s program guide for its data science master’s program, students who choose this discipline “work at organizations like Amazon, Green Bay Packers, CIA, Capital One, Google, MITRE, Morgan Stanley, NIH, McKinsey, Workday, Deloitte, Meetup, and Northrop Grumman.” They have titles like “machine learning engineer, senior data analyst, data scientist, deep learning researcher, data engineer, analytics consultant, data science developer, and more.”
Data science professionals can use their knowledge and skills in many ways and in almost every industry. You might specialize in business intelligence or robotics or healthcare informatics. There are almost too many options.
90 percent of data scientists hold master’s degrees, and 47 percent hold doctoral degrees. ( )
The Bureau of Labor Statistics sets median data scientist annual pay at just over $100,000. Top-paying sectors include ( ):
- Computer and peripheral equipment manufacturing ($148,290)
- Semiconductor and other electronic equipment manufacturing ($142,150)
- Specialized information services ($139,600)
- Data processing, hosting, and related services ($126,160)
- Accounting, tax preparation, bookkeeping, payroll services ($124,440)
|University and Program Name
There isn’t yet a set curriculum in data science programs. Some programs devote more credit hours to programming and math, while others spend more time on business intelligence. However, that will almost certainly change as more colleges and universities develop dedicated data science master’s degree programs.
Until then, the coursework in most full-time and part-time Master of Data Science programs will likely continue to cover topics related to data analytics, data engineering, applied statistics, quantitative analysis, and business intelligence. Students in these programs take core courses like:
Most data science graduate programs include a capstone course, research project, practicum, or internship requirements that allow students to address real-world problems related to computational data science. At Stanford University (which offers a Master of Science in Statistics with a data science track), for example, students must complete a capstone project, independent master’s-level research, or project labs in data science and analytics.
Some of the best master’s in data science programs can be found at:
You should also look into graduate schools with strong Master of Science in Computer Science programs or Master of Science in Business Analytics programs that offer a data science track. These programs are often identical in scope to data science master’s programs. It’s also possible to earn a Master of Business Administration in Data Science (University of Michigan – Ann Arbor’s Stephen M. Ross School of Business offers one). These programs are a good option for potential data scientists who prefer working on the management side to the tech side.
Master of Science in Data Science programs are still relatively rare. While data analytics programs and applied statistics programs often cover a lot of the same material, the best dedicated data science programs do have some features that set them apart.
First, the best data science master’s programs tend to be geared toward passionate professionals who already have robust analytics and statistics knowledge. At some colleges and universities, applicants must know multiple programming languages (e.g., Python, SQL, and R) and have an academic background and work experience involving information science, information systems, cloud computing, computer science, analytics, or statistics. Many programs only accept students who already have a working knowledge of the programs and tools data scientists typically use.
Second, the best data science master’s programs offer focused concentrations designed to give newly minted data scientists deep domain knowledge. Examples of specializations data science students can choose from include:
Third, the top data science programs tend to be offered not through business schools—as is often the case with data analytics master’s degrees—but through engineering schools, computer science schools, and data science schools.
Finally, the best data science master’s programs are offered by colleges and universities that can provide students with robust career support before and after graduation. They have relationships with employers and researchers. These make it easy for students to find high-value internship placements and make the professional connections that lead future opportunities.
You can study data science online at the master’s degree level, but you’ll only have a handful of programs to choose from if you want to enroll at a top school. There are strong online data science master’s degree programs at:
The curriculum in online data science master’s degree programs at these schools covers the same material as on-campus programs. However, you may miss out on valuable experiential learning opportunities and events designed to connect students with powerful industry insiders. You’ll learn everything you need to know to become a data scientist in an online program, but getting a job after graduation may be more difficult—even if you graduate from a relatively prestigious school.
Because data scientists have the skills and knowledge to work on various projects involving reporting, dashboarding, machine learning, data analysis, cyber security, and robotics, they can work in many roles. Some careers you might pursue after graduating with this degree include:
The roles outlined above don’t represent all the opportunities open to you after you earn a data science master’s degree. As one Reddit commenter put it: “The problem with the term ‘data scientist’ is that it is very loosely defined and covers many types of jobs. These jobs are not new, they have just been rebranded and cramped into one sexy title.” According to the poster, these jobs entail “two types of tasks: reporting and data visualization, [and] improving processes using math-heavy techniques. We used to call the former ‘business intelligence,’ ‘data analysis,’ ‘analytics’…” The second group “used to be called ‘machine learning specialist,’ ‘statistician,’ ‘actuary,’ and ‘operations researcher.'”
Clearly, getting a master’s degree in data science can lead you down many career pathways. You don’t have to stay in the data science silo to profit from this degree.
You’ll almost certainly earn more in this field after graduating from a top master’s program in data science… or data analytics, data engineering, applied statistics, or business intelligence. How much more isn’t exactly clear. The average data scientist salary might be about $99,000. But navigate away from PayScale to Glassdoor or Indeed or Salary.com, and you’ll find published averages closer to $113,000, $123,000, and $130,000. On the other hand, some data science jobs pay $70,000 or less.
This discrepancy is easy to explain. Data scientists tend to be well-paid. Still, there are plenty of companies that still don’t see exactly how data science translates into dollars, and so don’t want to pay top dollar for a data scientist. There are still more open data science positions than there are qualified data scientists, but opportunities aren’t evenly distributed. In areas where there’s a glut of data scientists, employers can pay less. On the other hand, data scientists in major metro areas tend to earn more, with the highest salaries concentrated in cities in California, Arizona, Idaho, New York, Mississippi, and Oregon. Experience matters, too; it may be that some salary surveys attracted more experienced respondents than others.
In other words, graduating from a dedicated data science program may not turn you into one of the top earners in this field—but it can’t hurt. The best data science master’s programs offer robust career support and access to large, active alumni networks that can lead to lucrative opportunities. Also, having a famous-name school on your diploma is never a bad thing.
Because there’s a shortage lack of fully qualified data science professionals, plenty of companies are willing to hire data scientists without advanced degrees. That said, if you go into this field, be prepared to compete for jobs against people with master’s degrees and PhDs. According to some sources, 88 percent of data scientists have master’s degrees and almost half have PhDs. That might not matter in areas where data scientists are scarce. In areas where major employers recognize the value of Big Data, however, not having graduated from at least a data science master’s program may be a real handicap. Think carefully before deciding to forgo an advanced degree in favor of a data science boot camp or certificate program.
At the same time, don’t merely assume that graduating from a master’s program—even if it is one of the best data science master’s programs—will set you up for life. Because technology is always evolving, becoming a data scientist involves more than just getting a degree. Data science degree programs evolve much more slowly than artificial intelligence, predictive analytics, programming languages, and data visualization tools do. Even the top data science master’s programs won’t necessarily teach you everything you’ll need to know to become a data scientist. At least some courses in those programs may be out-of-date by the time their students actually have their diplomas in hand. In other words, a degree in data science can launch your career, but that career will involve a lifetime of learning.
(Updated on January 9, 2024)
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