The Online M.S. in Data Science Experience

Meet four students who are transforming their careers through the Online Data Science, M.S. program. From a full-time professional moving cross-country, to a mathematics professor seeking new career depth, to a biomedical researcher exploring AI applications and a computer science graduate pursuing machine learning innovations, New York Tech students represent the diverse perspectives and ambitious goals driving the future of data science.

For the first three semesters of his data science master’s, Jaydin attended the New York Institute of Technology on campus in Long Island. When a job offer based in Oklahoma City arose, he wanted to find a way to continue the degree he started without giving up a valuable career opportunity. Fortunately, with some help from faculty and his advisor, Jaydin was able to transfer into the online program. Now, he works as a software development analyst and team lead for application development at Northrop Grumman, a multinational aerospace and defense company.

“The biggest value of the online master’s in data science program at New York Tech is the flexibility,” Jaydin says. “Being able to juggle full-time work while being a full-time student would not have been possible without the online program.” He also notes the value of asynchronous courses for allowing students to work on their own schedules.

“It also accommodates different learning styles by allowing me to learn the material on my down time, which allows for a more personal learning experience. It makes the program feel more like a hobby than a gruesome curriculum.”

Jaydin credits the program with teaching him skills like data mining, machine learning and predictive analytics. “With courses like Machine Learning, Introduction to Big Data, and Statistics for Data Science, the curriculum is very well rounded and provides an in-depth understanding of data science skills,” he says. “The professors throughout the curriculum are also very knowledgeable and willing to help you pass and learn.”

What started in a fine arts studio led Jaclyn to an unexpected destination in data science. After earning her first degree in fine arts, she discovered her passion for mathematics, pursuing a second bachelor's degree that launched her into a 13-year teaching career at Suffolk Community College. Now, as an assistant professor of mathematics and program coordinator, she's expanding her expertise into the world of data.

As an assistant professor of mathematics, Jaclyn saw an opportunity to expand her knowledge in a field related to her content area. She recognized that data science skills could help her students better understand mathematical applications, while also providing tools to analyze trends among her own student cohorts. The program's flexibility and the institution's strong reputation made it an ideal choice for her professional development.

As a mother of two children ages 9 and 6, Jaclyn carefully structures her study time around family life. She dedicates focused-learning hours between 9 p.m. and midnight after her children are asleep, as well as on Fridays and Sundays. Taking one course per cycle allows her to maintain this balance while progressing steadily toward her degree.

"My favorite course so far has been Statistics for Data Science. I really enjoyed using R programming to expand on my knowledge of elementary statistics and the group project proved to be a very positive collaborative experience. We were able to think creatively to develop models that made predictions about the relationships between variables."

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Jaclyn is already exploring ways to incorporate R programming into her elementary statistics courses and enhance her lecture presentations with data visualizations. She has found that her growing expertise in data science is opening new possibilities, both inside and outside the classroom.

Arafat's interest in data science grew from his experience in IT support and software engineering. After completing his bachelor's degree in computer science at New York Tech, he discovered his passion for data science while working on AI-powered applications and machine learning projects.

"After I graduated, the job market was really rough," Arafat shares. "I spoke to a lot of people, I joined a summer fellowship where I met with a bunch of software engineers...I saw that another job that you could transition into was a machine learning engineer. And then that was something that was also in my mind, like a career path that I wanted to be in in the next five years."

“My favorite course so far has been Programming for Data Science, because it was like my first proper introduction to Python and R," Arafat explains. "It was really fun because it covers data structures, data manipulation, and machine learning techniques.”

Through his coursework, Arafat has already completed several real-world projects, including analyzing New York City transportation data and developing fraud detection systems. "It was really fun, and I was able to draw so many conclusions and do so many analyses," he notes about the transportation project.

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Francis’s path to data science emerged from the laboratory, where his background in biomedical research repeatedly brought him face-to-face with complex data challenges. Working with laboratory rodents, he found himself analyzing everything from body weight changes to neural colony effects, handling increasingly massive amounts of data that required sophisticated analysis.

"What kind of got me to start thinking about data analysis specifically as a career track was being in the midst of so much daily data extractions and trying to comprehend how to do accurate statistics on some of the massive amounts of data that we were getting," Francis explains. "I had to rely on others to truly comprehend what was going on and get a full picture. And I didn't really like that. I wanted to expand above and kind of understand everything myself."

“For me and my career goals,” I wanted something relatively quick because I wanted to get my foot in the door as fast as possible, and to learn as fast as possible as much as I can,” he emphasized.

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"Statistics for Data Science has been my favorite course. Dr. Pam [Professor Pamelyn Witteman] has just been absolutely phenomenal," Francis shares. "She responds to every single student discussion post, every single comment from students and really cares about the people that are in her class. The application of mathematical skills with data analysis with team building has just been structured in such a way that I felt completely fulfilled with what I was given."

"The program really gave me the opportunity to learn SQL correctly and Python and Python structuring," Francis notes. He's already applying these skills to work he’s doing outside of the program, with a particular focus on writing code that's properly structured and easily understood by others.

These students represent the diverse perspectives that make the Online, M.S. in Data Science program unique. From Jaydin’s cross country transition to Jaclyn's journey bridging fine arts and mathematics education, to Francis's transition from biomedical research, to Arafat's evolution from IT support to machine learning–each brings their own experience and goals to the program.

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