Who Drives the Value of Top Master’s in Data Science Programs? Assessing the People Behind the Program.

June 29, 2021

Conventional wisdom states that success is a matter of who you know, not what you know. In data science, success hinges on both. Ninety percent of data scientists have advanced degrees — suggesting a discipline with high respect for formal education — but a Master of Science in Data Science (MSDS) isn’t enough to launch a career. Relationships drive opportunity and innovation, and building a robust professional network is equally as important as developing a knowledge base of technical data science skills.

Gauging the intangible value of various degree programs isn’t as simple as weighing tuition costs against future earning potential. The people behind a program drive the return on investment of a degree. Mindful of this, Stevens Institute of Technology does everything possible to facilitate virtual relationship-building between the distinguished faculty leading its online MSDS (and all other graduate degree programs) and the diverse cohorts of career-focused students, who eventually become engaged alumni.



“Who’s teaching?” is the first question to ask. The best teachers are doers. Stevens’ data science faculty includes experts in stochastic optimization and cryptography. Students learn from highly regarded leaders, such as Rizos Sklinos and Shusen Wang, who are investigating and developing future-forward tech in data science and data engineering.

Faculty access is another critical variable. In theory, class sizes in online master’s in data science programs are limited only by the capabilities of digital learning platforms. However, StevensOnline graduate programs take a conservative approach, similar to that of highly selective on-campus programs. The student-to-faculty ratio is just 25:1, which is small enough to ensure distance learners develop relationships with their professors and other Schaefer School of Engineering & Science faculty and staff.

What happens behind the scenes? To say that data science is a rapidly evolving field is an understatement, and it’s not enough for professors to have backgrounds in data analysis, data mining, information systems and computational methods. For example, industry trade journals regularly publish Stevens’ Associate Professor Michael Zabarankin‘s ongoing research into risk management and optimal control, continuous and discrete optimization, mathematical physics and variational principles. Thought leaders such as Zabarankin are at the helm of the best MSDS programs, tackling real-world data science problems. They also bring relationships and partnerships with top employers and influential organizations in data science. StevensOnline has a track record of placing MSDS graduates at notable tech companies such as Amazon and financial firms such as Bank of America, in part because of faculty connections.

You will advance further and more quickly if you acknowledge the career-enhancing power of relationships in graduate school and beyond.

A final metric to consider is representation. Women are notoriously underrepresented in data science, and Stevens proactively promotes gender parity. Department of Mathematical Sciences Chair Darinka Dentcheva is an acclaimed researcher in stochastic optimization and control using mathematical models of risk and their applications, and 29 percent of current faculty are women. The best professional networks are diverse.


Top MSDS programs nurture relationship-building through group coursework and project work so students can develop career-boosting professional networks. Stevens’ Master of Science in Data Science program stands out when it comes to peer-to-peer engagement. Highly intelligent, motivated students bring years of professional experience solving large-scale, real-world problems to each cohort. All data science students begin the master’s degree program (whether online or on-campus) ready to learn from one another. Stevens is also intentional about fostering interdisciplinary collaboration through cross-departmental research by faculty and students. Innovation and entrepreneurship events unite MSDS, bachelor’s degree and Ph.D. candidates on experience-building projects spanning healthcare, cybersecurity, engineering, data science and analytics.


Stevens attracts professionals who already have significant computer science, analytics and data science experience, which means the university’s global alumni network is substantial. Students who connect and work together after graduation can accomplish great things — especially given the postgraduate support alumni receive. Graduates of the part-time, online data science program receive the same job counseling, networking assistance and support as full-time students studying on campus. Online Master of Science in Data Science graduates can join the same alumni groups, connect with potential employers, meet with career advisors, and participate in events and workshops that provide new chances to make valuable professional connections.


Top MSDS programs support ongoing research in data science, and in some cases, students can participate in those research projects. Stevens Institute of Technology filed 25 provisional patents in 2020, and graduate students contributed to some of that work — gaining valuable insights into the forces driving the evolution.

Even if research isn’t among your academic priorities, it is still worth knowing how faculty research can shape the future of data scienceSamantha Kleinberg of the Department of Computer Science at Stevens, for example, is looking for more efficient ways to analyze unwieldy time-series datasets generated by neurological intensive care units. Her work has applications outside medicine and may eventually influence data science in other disciplines.


Program content and format are just as important as the people in it. The best data science master’s programs tend to be highly technical, heavy on mathematics and offered by engineering or computer science departments. StevensOnline doesn’t require that MSDS applicants be proficient in programming languages and platforms such as Python, R and MATLAB before enrolling, but many incoming students are comfortable with them when they apply. Additionally, most pursuing a graduate-level data science degree have experience with multivariable calculus, linear algebra, probability and statistics, and how to use frameworks such as Apache, Hadoop, Hive and Mahout and data visualization tools such as D3.js and Tableau.

Core data science courses in top MSDS programs cover topics such as:

  • Advanced optimization methods
  • Algorithm development
  • Analysis review
  • Artificial intelligence
  • Big Data
  • Cloud computing
  • Data management
  • Database systems
  • Deep learning
  • Distributed systems
  • Dynamic programming
  • Languages such as Python and SQL
  • Linear algebra
  • Machine learning
  • Natural language processing
  • Predictive analytics
  • Probability theory
  • Quantitative analysis
  • Reinforcement learning
  • Statistical methods

Programs geared toward more experienced students are often formatted to meet the needs of busy professionals. The flexibility of Stevens’ 100 percent online MS in Data Science is ideal for those students who plan to continue working in full-time jobs as they pursue degrees. Most distance learners enrolled in Stevens Institute of Technology’s Charles V. Schaefer, Jr. School of Engineering & Science complete the 30-credit, 10-course online MSDS in five semesters when they take six credit hours (or two classes) per semester. The commitment involved is manageable even for busy professionals. Students devote approximately nine to 12 hours per class per week to their studies, including about one-and-a-half hours of live sessions plus five hours of self-paced coursework and three to five hours of homework, project work and study time.

Ultimately, the value of a master’s in data science is the same whether you earn it part-time, online or on-campus — provided you choose a program that prioritizes not just the curriculum but also the people. There’s a human side to data science that is easy to overlook, even as you dig more deeply into what MSDS programs have to offer. You will almost certainly advance further and more quickly if you acknowledge the career-enhancing power of relationships in graduate school and beyond.