Master of Data Science Salaries: 2026 Guide

Key takeaways

Earning your Master of Data Science degree can lead to lucrative compensation packages, especially for senior-level or managerial roles.

• The US Bureau of Labor Statistics projects that data scientist roles will grow 34 percent between 2024 and 2034 [1]. 

• A Master of Data Science degree typically takes between one to five years to complete, depending on your pace.

• You can boost your earning potential by building experience in data science, living in high-demand areas like Silicon Valley, and choosing top-paying industries.

Explore what you can expect to earn with a Master of Data Science degree to decide whether this in-demand degree is the right fit for your career and lifestyle goals. 

The impact of a master’s degree in data science on salary

In general, having a master’s degree has been shown to positively affect your salary. Master’s degree holders earn a higher median salary than bachelor’s degree holders, taking home $1,840 compared to $1,543 per week [2]. 

The National Association of Colleges and Employers found that a graduate degree can be financially beneficial [3]. The related field of computer science saw significant returns for students. Bachelor’s degree graduates were expected to earn a starting salary of $74,778 in 2024, but that number jumped to $85,403 for master’s degree graduates [3]. 

Data science is a high-growth industry, with the US Bureau of Labor Statistics (BLS) projecting data scientist roles to grow 34 percent between 2024 and 2034 [1]. While you can enter some data science roles with a bachelor’s degree, the BLS notes employers may prefer applicants with advanced degrees, meaning a master’s degree in data science could set you apart [1].

STEM (science, technology, engineering, and mathematics) careers are among the fields that typically pay more for advanced education, according to the BLS [4]. Thirty-four percent of data scientists hold a master’s while 51 percent have a bachelor’s degree, according to Zippia [5]. 

What is data science?

Data science is a field at the intersection of data analytics, statistics, artificial intelligence, computer programming, and machine learning. Within this industry, you use advanced methods to uncover insights from large volumes of complex data. This may involve describing what your data shows, predicting future outcomes, or even generating suggestions on how organizations can best respond to these future predictions. 

3 factors that influence a Master of Data Science salary

Even with a master’s degree in data science, several factors impact your earning potential. 

1. Experience 

Becoming a data scientist often requires a bachelor’s degree in a related field. A master’s degree can be a valuable credential to add to your resume, but beyond your education, experience goes a long way in a data science career. 

An entry-level data scientist (up to one year of experience) earns a median annual salary of $133,000, according to Glassdoor [6]. The more experience and education you amass, the higher your paycheck will likely be because you may qualify for senior-level and managerial roles. For example, Glassdoor reports that the median salary for highly experienced data scientists (15+ years of experience) is $234,000 [6]. Those salaries can be even higher if your role involves managerial responsibilities. 

2. Location

Where you live can often determine how much you will earn. While a company will consider your education and experience when making an offer, your location can also affect your total master’s in data science salary. 

For example, data scientists in California and the Pacific Northwest tend to earn higher salaries than those living in Texas or the southern United States, according to Zippia [7]. But the cost of living is also higher in these areas. 

Tech companies tend to pay higher salaries across the board. For data science professionals who work in tech, the top cities for salaries in the US as of 2024 are [8]: 

3. Industry

Lastly, the industry in which you work can impact your salary with a master’s degree in data science.

The top industries for data scientists are [7]: 

1. Start-ups

2. Technology

3. Retail

Other top-paying industries are manufacturing and finance.

Jobs you can pursue with a master’s in data science

Thanks to the advanced nature of a master’s degree, you may find that you qualify for senior- and managerial-level data science jobs. 

Learn more about the types of salaries you can make as a: 

• Data analyst

• Machine learning engineer

• SQL developer

• Statistician

• Data engineer

Read more: Data Science Jobs: Resources and Career Guide 

How long does a master’s in data science take?

A master’s in data science program takes one to five years to complete, depending on your pace. Part-time programs allow you to work while earning your degree, but they’ll take longer to complete. You can also opt for an accelerated, full-time MS in data science program, which you can complete in one to two years.

Other ways to advance your knowledge of data science

When you’ve already earned your bachelor’s degree but are interested in pivoting to a career in data science, a master’s may be beneficial. Many programs provide a foundational overview of the skills needed to succeed: statistics, knowledge of a programming language, and the ability to work with data sets.

But when you’ve been working in data science for some time, an advanced degree may be more useful if the program offers you an opportunity to concentrate in an area such as machine learning or bioinformatics. The specialized knowledge you gain can lead to careers in in-demand fields, such as AI. 

Learn more about whether a master’s degree in data science is worth it when it comes to your goals. Beyond a graduate degree, there are other ways to strengthen your knowledge of data science, either at a foundational or specialized level. These include: 

• Certificates: Strengthen your skill set by earning a Professional Certificate (through a leading company) in data science or an area of data science. Certificates are often designed to take less than one year to complete at a much lower cost than a graduate degree.

• Courses: Enroll in a massive open online course (MOOC) to acquire or improve your knowledge of data science. These individual courses can be completed in a few weeks to a few months, depending on the time you have to commit, and are typically designed to emphasize skills development. 

• Projects: Find projects online on YouTube or via Guided Projects on Coursera.

• Books: Find and read books on the area of data science you’re interested in learning. Not sure where to start? We’ve compiled lists of books on data analysis and books on machine learning to help point you in the right direction. 

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