MSDS Grads 'Have Something the C-Suite Can Use'

Professional photo of Kirill Prokrym

Once, all roads led to Rome. These days, it seems they all lead to careers in data science. The big data deluge of the twenty-first century has created opportunities for strategic data analysis in every digitized field — which, in this digital era, means practically every profession.

That's why data science programs attract students from so many different backgrounds. Stevens Institute of Technology master's candidate Kirill Prokrym, for example, began his career studying cancer in a biomarker lab. When he discovered that he "enjoyed the programming and data analysis side more than the bench chemistry side," he began to explore other options. His search led him to the Stevens Online Master of Data Science program.

Prokrym saw the master's as an opportunity to broaden his career prospects. He also loves the exposure to new, innovative data analytics approaches. And, he appreciates how quickly students can complete the program — in just 20 months, for those who take two classes per semester.

You came to data analysis from a medical perspective. Is medicine still your focus?

In the long term, probably, although I'm keeping an open mind. I would 100 percent enjoy working in the medical field again doing some sort of biological or genetic data — anything like that would be in my wheelhouse. That said, Stevens is in Hoboken, right across the river from New York City, and it has strong ties to the finance sector.

There are certainly opportunities for data science in finance.

Absolutely. Also, a master's in data science is a foundational degree. If you want to pursue anything else or develop a higher-level specialization, you can flip the degree to do something more focused on machine learning, artificial intelligence or higher mathematics.

The big data explosion has created a lot of opportunities.

Correct. The beauty of data science is that it takes three separate disciplines and pulls them together. You need statistics, you need computer science and you need business skills. When you combine these three disciplines and translate them into action items, you have something the C-suite can use.

It's not simple. You need to be able to pick models based on the problem you're trying to solve. You can't just choose any old statistical model; it has to match the type of data you're pulling. Also, you spend a lot of time on data cleaning and exploratory data analysis. It's all part of the process. If you aren't a confident, capable programmer, you'll never get through the data cohesively and accurately to turn it into something usable.

Additionally, you need a statistics background to achieve your goals. If you can't match a model to the kind of data you're getting, or you don't know that you should ask your business partner for different data, you'll never get valuable insights.

In data science, you can lean into any of three strengths. You can stress the machine modeling part and get further into creating algorithms. Or, you can develop your business analytical skills on the data presentation side — become a professional data storyteller, in a sense, dashboarding data to make it accessible to your company. Your third option is to become a data engineer, collecting data, setting up processes for your company and building the schemas for how your data is collected and stored. As we reach the point at which companies have so much data in their warehouses, it becomes crucial to set up those structures and allocate data intelligently from day one.

Why did you choose to attend an online program?

Well, COVID-19, for one. The pandemic began to ramp up when I started the program, and vaccines weren't available to everyone. It was just safer to take classes from home. With variants popping up now, I'm still pretty happy with my decision.

Stevens' flexibility made the decision easier. You can switch over and become an in-person student any time if you want. And, you have access to the campus regardless. Knowing I could change over to full-time and on-campus if I wanted to was a great benefit. That said, I prefer online. As a full-time worker, I need the extra flexibility online study provides.

What specifically about Stevens' online master's program most appealed to you?

I'm particularly interested in the statistical basis of data science. At Stevens, the department head is a mathematician whose research is in stochastic processes. The program stresses the importance of building a solid statistical foundation for data science. As someone who wants to do modeling, I thought that was crucial.

Some prospective students worry that online study means working in solitude. What does Stevens do to promote online student interaction and collaboration?

Every student has a Success Coach who organizes introductions and is happy to organize study groups. My coach made sure my fellow students and I met each other. She offered to create Discord groups for us, send out Zoom group chat invites, set up Microsoft Teams and email our professors on our behalf. She also made sure we were signed up for classes. Everything she did had a community support angle, which made everything so much easier.

I strongly recommend attending office hours. You'll get extra attention from your professors and meet any other students. You'll work through problems and solve questions together, and you'll see where your strengths and weaknesses lie.

Additionally, all classes have a collaborative aspect. Students work on homework assignments together. Graduate work, by its nature, is collaborative; it's more discussion-based than undergraduate learning. You're encouraged to interact, even during class time. Live sessions tend to focus on identifying students' pain points and helping us work through the challenges.

What has surprised you the most about your learning experience at Stevens?

How challenging the material is at times. Because it's a multidisciplinary field, we have people from all different backgrounds in this program. Everyone has strengths and weaknesses: someone is a better mathematician, another one is a great statistician, a third student is an outstanding programmer and another excels at business intelligence. We have people from finance sectors, academia and research. We have people working full-time jobs as analysts in other sectors. Everyone has something to contribute and areas where they need help.

Anyone coming into this program should prepare to face complex problems. Sure, some weeks, you'll pick things up really quickly and everything will click. Then the next week, you'll come across something that really challenges you — maybe central limit theorem or something like that. It's essential to your success to understand these foundational concepts. You can't just breeze through.

What advice would you offer students entering the program?

Review your undergraduate statistics and mathematics before you start. Make sure they're solid because the first semester focuses on both. Also, make sure you're ready for the online format. You need to communicate digitally with faculty, classmates and your success coach. Be comfortable reaching out and making connections. Make sure you're putting yourself out there for opportunities. Don't hold back and miss out on a great moment.

Final question: Why a master's program as opposed to a bootcamp or certificate?

I've been through bootcamps, so I can speak from experience on this. Bootcamps focus on the raw application of concepts. They often don't have the time to really dig deep into why, say, an L2 norm works the way it does. They explain how to use it but not why.

In data science, you're applying a statistical model, and you really need to understand why you're choosing that particular model. It's not as simple as following a flowchart that says, "If it's this kind of data, use linear regression." The master's trains you to make decisions intelligently. Remember, data science is a moving, living, breathing career. It constantly incorporates new technology and new concepts. The beauty of getting a master's is that you'll always understand what those tools are doing, even as the tools change.

The Online Master of Science in Data Science (MSDS) at Stevens Institute of Technology develops data scientists adept at Python and R, SQL, Hadoop, Hive and TensorFlow. The 30-credit-hour, 10 course curriculum digs deep into machine learning, deep learning, natural language processing, data visualization, and advanced statistical methods. The program, which is delivered 100 percent online and is typically completed in 20 months, offers two pathways: a traditional path for those with limited data science experience and an advanced path for those with more-developed skills.

Stevens Institutes's online programs were named the nation's eighth-best online graduate computer information technology program by US News & World Report in 2021. The same publication ranked Stevens' online graduate engineering programs 21st and third-best in the state of New Jersey (among engineering and science graduate programs). Learn more about qualifications and the admissions process from the admissions office or simply start your online application today. A world of innovation awaits you.