Should You Get a Master’s in Data Science Just Because Your Company Pays for It?

November 18, 2021

If you are already an experienced mid-career professional in advanced analytics, data science or a related role, you may not feel strongly driven to pursue graduate education. While 90 percent of data scientists have advanced degrees, there is still a global shortage of Big Data talent. Coupled with growing demand for data scientists, that talent shortage has created an employment landscape in which job seekers have the advantage. Consequently, you may find yourself facing a quandary if your employer offers to pay for an on-campus or online master’s in data science. For many professionals, tuition is a leading consideration, but if you are earning a comfortable income, the promise of tuition reimbursement may not be a compelling enough reason to enroll in a part-time graduate program.

Before you reject that offer out of hand, however, consider that nearly half of all data science job postings across the U.S. require that applicants have a Master of Science in Data Science (MSDS) or a related degree. Based on this statistic alone, it is not hyperbole to claim that the MSDS is now the entry-level degree in data science. It is also increasingly an academic credential even seasoned data scientists must have to remain competitive in the field.


The surprising answer is no. Top on-campus and online master of data science programs are rigorous, demanding and geared toward students driven by internal motivation and an interest in the power hidden in information. Flexible, online programs such as Stevens Institute of Technology’s MSDS attract applicants with strong academic and professional experience in data analytics, data visualization, business intelligence, business analytics, information technology, information systems, computer science and statistical mathematics. They apply because they want to advance in analytics careers or leverage the data generated in their professional spheres more adroitly.

If it happens they are eligible to take part in employer tuition reimbursement programs, that is just an extra incentive—and not a particularly big one. Employer-sponsored tuition reimbursements are often capped at $5,250 annually because tuition assistance above that amount is taxable as income.


Here are five reasons that may resonate with you, wherever you are in your data science career:


More highly trained data scientists exist today than when LinkedIn reported in 2018 that 150,000 jobs for data scientists would go unfilled, which means the competition for open positions has grown more intense. The talent gap in data science is narrowing, but the regions where demand for data scientists still outstrips supply are not equally distributed around the U.S. High-paying jobs in data science are clustered in established and emerging technology hubs, and the cities in which data scientists earn the most often have no shortage of tech talent.

If you work in a region where numerous qualified data scientists compete for the same jobs, differentiating yourself from your peers is crucial. Having a graduate degree on your resume will help you move past the HR filters at high-profile, high-paying companies such as Amazon, Dropbox and Netflix. Credentials alone aren’t enough, however. Employers look for specific skills in data team hires, which is why you must choose a data science master’s program such as Stevens Institute of Technology’s online master’s in data science, which teaches critical interdisciplinary skills related to programming, data analysis, complex mathematics, statistics and problem-solving.


Data science is a rapidly evolving field shaped largely by disruptive technology, and keeping up involves continuous study. As Burning Glass points out in its Quant Crunch report, “This reality requires a new type of workforce and attitude from both employers and employees around continuous learning and mastering skills that will enable employees to be prepared for not-yet-arrived jobs of the future.” Innovations such as automation, Natural Language Processing, intelligent machines and Federated Learning are just some of the relatively recent advancements in data science that boot camps, certificate programs and MOOC sequences seldom cover. Self-study is no longer all it takes to break into or advance in this field.

Enrolling in a top data science graduate program is a straightforward way to refresh or update your skillset and master the latest data science techniques and technologies. Stevens’ future-focused interdisciplinary MSDS curriculum gives online students the leading-edge skills employers look for today (e.g., machine learning and artificial intelligence skills, data mining skills and deep learning skills) and prepare for the iterations of data science they will encounter in the future.


Success in data science is about who you know as well as what you know, and pursuing a master’s in this discipline can enhance your career in both areas. Stevens’ data science faculty includes experts in areas of data science and data engineering such as stochastic optimization and cryptography. The student-to-faculty ratio in the online master’s in data science program is just 25:1, so you can make meaningful connections with your professors and other Schaefer School of Engineering & Science faculty and staff.

Stevens Institute of Technology takes networking seriously and does everything possible to facilitate relationship-building between the distinguished faculty leading its online MSDS, diverse cohorts of career-focused students and alumni who studied data science online and on campus. MSDS candidates in the online degree program are knowledgeable technologists and bring years of real-world experience to group coursework and project work. The projects you do together will enrich your academic experience, and the relationships you build through that work can lead to a wealth of future opportunities. After graduation, you can join alumni groups, connect with potential employers, meet with career advisors and participate in events and workshops that provide opportunities to make valuable professional connections.


Data science has a reputation for being a field where high salaries are standard, and mid-career data scientists with the proper credentials typically earn over six figures. One salary report from Burtch Works found that entry level data scientists earn about $95,000, which seems impressive until you consider that many “entry level” Big Data jobs are filled by experienced data science professionals with master’s degrees. Employment data suggests that data scientists earn substantially more than the average annual wage in the U.S. at all levels and also have advanced degrees at all levels.

Not having a master’s can negatively impact your earning potential in this field. Even if you earn as much as your peers in your current position, there may be promotions and pay increases you can’t access because you don’t meet education requirements. Consider that senior data scientists can earn $165,000. A data science director can earn $173,000. And a vice president of data science can earn $203,000. Those figures also come with increased job security. According to the U.S. Department of Labor, Employment & Training Administration, employers will create new jobs for data scientists with master’s degrees at a rate much higher than the average for all occupations over the next 10 years.


There are very few technical barriers keeping data scientists in the office, and some of the companies with the largest data-related workforces also have generous remote work policies. Those companies don’t trust their data to just anyone, however. Research suggests that across industries, employers with work-from-home and work-from-anywhere policies look for workers with top-notch credentials, advanced applied data science skills and significant work experience.

The U.S. Bureau of Labor Statistics’ 2019 American Time Use Survey found that employees with advanced degrees were more likely to work remotely than employees with bachelor’s degrees and other undergraduate degrees, and that close to half of all workers with advanced degrees work remotely some of the time. Full-time work-from-home positions are still relatively rare in this field, but your chances of landing a remote data science job will be significantly higher with an MSDS on your resume.


There is nothing inherently wrong with pursuing education for education’s sake. Data science is an exciting field — and an evolving one, which means there will always be something new to learn. Moreover, data science is a discipline that requires a great deal of curiosity and creativity in addition to technical knowledge. One Kaggle survey found that 70 percent of data scientists who pursued on-campus and online master’s degrees did so not for the diploma or the salary boost but to “gain more knowledge.” If your primary motivation to pursue an MSDS is the desire to learn as much as you can about it, lean into that. The Kaggle report concluded that passionate interest in data science and the desire to learn more are probably the best reasons to pursue a master’s in this field.


There’s no question that advancing in data science requires up-to-date technical skills, advanced mathematical skills, software engineering skills, a strong network, a commitment to learning and an advanced degree. The best on-campus and online Master of Science in Data Science degree programs are highly technical, heavy on mathematics and offered by engineering or computer science departments and populated by students who know what this degree will do for their careers.

Finding your motivation is the key to success because choosing a program as rigorous as the StevensOnline MSDS involves making a serious commitment. The flexibility of Stevens’ 100 percent online master’s in data science program is ideal for those students who plan to continue working in full-time jobs as they pursue degrees, but the curriculum is challenging and geared toward advanced learners. The ideal applicant is already proficient in programming languages and platforms such as Python, R and MATLAB, familiar with frameworks such as Apache, Hadoop, Hive and Mahout and comfortable using data visualization tools such as D3.js and Tableau.

Even if your employer offers to shoulder some or even all of the cost of a Master of Science in Data Science, think carefully about whether you meet the admissions requirements before applying. You should also consider whether this is the right degree for you — and if you are ready and able to commit to a demanding graduate program. There are many good reasons to pursue a data science master’s degree, but while tuition assistance can make the decision to enroll in an MSDS program easier, it shouldn’t be the deciding factor.