What Kind of Salary Can You Expect with a Master’s in Data Science?

In 2012, Harvard Business Review named data scientist the “sexiest job of the 21st century,” and the truth is that it continues to be one of the hottest professions: the US Bureau of Labor Statistics (BLS) predicts 36% growth in employment of data scientist by 2031, over 7x the growth rate for the US labor market as a whole. Unsurprisingly, given this demand, recent data scientists' salaries are well above average, with the BLS’ 2021 median estimate of $100,910 more than doubling the average American’s annual wages.

Of course, the promise of a booming job market and high compensation has many eyeing a move into the field. For those in this situation, a master’s in data science seems a surefire way to set themselves apart and, eventually, cash in.

But underneath the hype, is a graduate study in data science a sound investment? How much — or how much more — can you make if you can list this academic credential on your resume?

In this article, we’ll provide insight into the typical master's in data science salary and explore whether the degree's benefits justify the costs.

What’s a master’s in data science?

A master’s in data science is a one- to two-year graduate program that combines coursework in computer science, applied mathematics, data science principles, and more with opportunities for practical application through capstone projects, internships, and practica. While a graduate of a data science master’s program will often go on to become a data scientist, other potential career paths include data architect, data engineer, data analyst, business analyst, and business intelligence analyst. For more, see our article on data science jobs.

Master’s in data science curriculum

Students in a data science master’s program can expect coursework in the following areas:

Computer science and information technology, including courses on programming, data visualization, artificial intelligence, machine learning, and database management

Applied mathematics, including courses on probability, statistics, linear algebra, and big data analytics

Data science principles, including data management, research design, and data science ethics

Industry-specific electives such as marketing analytics, financial analytics, etc.

Master’s in data science modality

Historically, master’s programs have been offered in person. However, more and more data science programs are being offered online or in hybrid modalities. This follows a larger trend in higher education: between 2000 and 2016, the share of students attending a master’s program in remote or hybrid capacity grew from just 13% in 2000 to 52% in 2016. As the dust clears after the COVID-19 pandemic, we’ll likely see this trend only accelerate.

The ability to study data science online doesn’t merely make education from a world-class university accessible to aspiring data scientists around the world: as you’ll see presently, it can also offer potential cost savings.

Master’s in data science cost

In the US, the average total cost of a master’s of science degree is $61,200, according to data provided by educationdata.org. However, it’s important to note that modality can play a big part in how much you pay — and thus your eventual return on investment. By studying online, you may be able to continue working and avoid relocation, cutting out lost income potential and the costs associated with moving and potentially paying higher rent. Ultimately, these cost-savings can make pursuing a master’s degree possible for those who are more cash-strapped or need to support family members and other loved ones.

Why pursue a master’s in data science?

Of course, $60,000 is no small investment, even if you earn a salary while studying. Given this cost, why do those interested in data science pursue a master’s degree? In short, whether you’re looking to transition careers or advance your career, a data science master’s degree opens the opportunity to pull a salary that many decide is a sufficient return on the up-front cost of education. We’ll dive into each group in turn.

Career transition

Many who transition into data science are dissatisfied with their current earning potential. Perhaps they are in a low-paying industry or feel blocked by their management, and there is no easy way to move laterally to another company. Provided they hold a bachelor’s degree, even if in an unrelated social sciences or humanities field, the good news is that many can gain admission into a data science master’s program and slingshot themselves onto a higher-earning career path. Many data science programs provide resources like pre-program computer science and mathematics courses to ease these kinds of transitions.

Career advancement

For those already in the broader field of analytics — maybe they are working as a junior data analyst, business analyst, or data scientist — a data science master’s can allow them to apply to data science jobs that offer a higher salary and more responsibility. In fact, for senior data scientist positions or executive positions like analytics manager or chief information officer, many companies list a master’s in data science or a related field as a prerequisite in job descriptions. In reality, however, it’s a prerequisite for most data science jobs: over two-thirds of data scientists surveyed in a recent Burtch Works study reported holding a master’s degree.

But how much more can you earn after a data science master’s degree? We’ll dive into that next.

What’s a typical data science master’s salary?

Given that the majority of data scientists hold a master’s degree of some sort, it can be difficult to pin down exactly the average data science salary for a holder of the degree: Burtch Works’ estimate for the median base salary of a level 1 individual contributor data scientist holding a master’s degree ($90,000), for example, is the same as its estimate of median salary not controlling for education.

The takeaway? If you want to earn a data scientist salary, you’ll likely need to get a master’s degree at some point. But does this make financial sense? While a $90,000 base salary might not seem like much compared to an upfront cost of $60,000 and potential temporary loss of income, it’s crucial to remember that after earning your master’s degree, if things go well, you’ll be able to pull this kind of base salary every year until you retire.

Moreover, this is just an estimate of a base salary for the lowest data scientist level. In reality, your total compensation would likely be higher once you factor in bonus, benefits, equity compensation, and growth potential. Burtch Works’ estimate for the base salary of a level 3 individual contributor holding a master’s degree grows to $140,000, for example, and the median base salary for a data science or data analytics manager holding a master’s degree starts at $150,000, with a level 3 manager earning $260,000.

It’s worth noting again that a data science master’s doesn’t only prepare you for a career as a data scientist: with the training you get at graduate school, you gain the skills to feasibly apply to machine learning engineer, data engineer, data architect, and senior business analyst roles, either right out of school or down the road. As with data science, the salaries in these positions are extremely high. For ease of comparison, we’ve used data from Salary.com below.

Data scientist: $140,672
Machine learning engineer: $121,788
Data engineer: $113,929
Data architect: $126,274
Senior business analyst: $86,514

To learn more about these roles, check out our relevant guides:

The bottom line: is a master’s in data science worth it?

We’ve explored what you’ll learn in a data science master’s program, the reasons for pursuing a graduate degree in data science, the costs associated with doing so, and the range of salaries master’s degree holders in data science have access to.

So, is it worth it? Ultimately, you’ll have to decide whether you have sufficient aptitude for computer science and advanced mathematics to perform well. Can you build a professional network to maximize your chances of getting a high-paying job? Do you have the cash to make the up-front investment, or are you willing to finance your education with loans? If you can answer yes to these questions, then there’s a good chance that pursuing a data science master’s will be worth it for you. If things go well, you can turn a $60,000 one-time cost into a salary offering a return on investment anywhere from 50% to over 300% every year.

How do you maximize your chances of success? The first step is to find a program that will work for you. Many factors contribute to this decision, including the program's cost and modality, alumni's success rates, the requirements and prerequisites for applying students, the location, and the department profile.

To jump-start your program research, we recommend you check out both our guide to data science master’s programs and our guide to online-only data science master’s programs. These guides explain in greater detail what you should expect from a data science master’s and what to look for in a program. We also provide our top picks: programs that we think can best serve students from various backgrounds.

If you’re interested in learning more about a typical data science career path, we have an article that outlines what’s involved in moving from an entry-level or junior data scientist position to a senior data scientist position to, finally, an executive position like chief data officer or chief information officer.

If you’re interested in diving more deeply into landing your first data science job, check out our explainer on how to become a data scientist.