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Interview with Michael McCarthy, Ph.D. - Director of the Master of Science in Data Science (MSDS) Program at Utica College

About Dr. Michael McCarthy

Dr. Michael McCarthy is an Associate Professor at Utica College, where he serves as Director of the school’s Master of Science in Data Science (MSDS) program. He holds a PhD and a master’s degree in Geography from the University of North Carolina at Greensboro and a Bachelor of Science in Geographical Information Systems (GIS) from the United States Military Academy at West Point. His thesis was a quantitative analysis of the airline industry by metropolitan area and his dissertation provided qualitative and quantitative analyzes of creative workers in the US. Dr. McCarthy served as an aviation officer in the US Army and served in the Army’s Training and Doctrine Command, where he analyzed future global trends. Prior to assuming his position at Utica College, he applied his skills as a Program Analyst for the US Department of Veterans Affairs.

Interview Questions

[] Before we launch into the main questions, can you provide some insight into how your training in geography and your experiences in the military led to a career as a data scientist?

[Dr. McCarthy] One of the great byproducts of my academic work at West Point was the introduction to the geographic and engineering mindsets. A geographic understanding is not common because it is not generally emphasized in American high schools. My studies in the geographic information science major really helped me understand that space and place matter; context matters. My environmental engineering minor helped me understand the methodical process for problem solving. Each mindset is distinctly different and served me well in my professional and academic pursuits.

After my undergrad, I went to the Army’s flight school to learn to fly helicopters. It was a challenging year of learning yet another new way of thinking and refining my coordination. I have not flown since 2005 but I retain a pilot’s mindset with a focus on technical proficiency that comes from practice and persistence. I also love checklists, as all pilots should.

I gained a lot of operational experience in the Army that helped me learn the team-building skills to complete complex tasks. My operational experience culminated when I lead an aviation platoon in combat. I also had the unique opportunity to work as part of an Army think tank that contemplated the economic, demographic, and agricultural situation for the world in 2050. This was exciting research based on data. It really opened my eyes to the power of data and the knowledge that can be coaxed from it.

After my honorable discharge from the Army, I could have gone to graduate school for a multitude of subjects, but geography had a hold on me from my undergraduate work, which was reinforced by my work in the think tank.

In my time as an analyst for the Department of Veterans Affairs (VA) I worked on many projects. At the time, the VA was the quintessential example of DRIP: data rich, information poor. The VA is awash with data in multiple legacy structures and finding meaning in the unruly, unstructured data was always a challenge. The best part about each project was its worthy focus: better patient outcomes for our Veterans, more efficient clinic operations for better use of tax-payer dollars, and improving employee wellbeing and work experience.

Additionally, I served as a change agent enabling a culture shift toward data-driven decision making; this was by far the most challenging of my duties. It was great work with a great team and I would still be at the VA if I did not have the opportunity to teach.

[] Can you offer an overview of Utica College’s Online MSDS program in terms its design and structure and from the perspective of what students experience?

The goal of Utica College’s MSDS is to enable students to harness their curiosity and persistence to hone new skills to become change agents for any organization. The trajectory of Utica College’s MSDS program follows the data science process while teaching the three main components that make a successful data scientist: quantitative skills, computer science, and a particular domain where a student plans to apply their skills, like healthcare, business, or governmental organizations.

The goal of Utica College’s MSDS is to enable students to harness their curiosity and persistence to hone new skills to become change agents for any organization.

The first course (DSC 501) serves as an introduction to data science, the MSDS program, and graduate school in general. The course really stresses the fundamentals, like the scientific method, ethics, bias, and social responsibility. The scientific method is applied toward a student-generated course project; it is amazing to see the complex questions students analyze. We dig into ethics because the data science discipline is still developing ethical baselines; as people’s data become increasingly commodified, a strong ethical understanding helps students discern what is appropriate use of data and what is less appropriate or even unethical or illegal.

Students are encouraged to ask “why” a lot. The process of curious investigation trains students to constantly question each aspect of their analysis, from the basics, like the data’s units, to the intricate goals of analysis, “Why are we doing this analysis?” or “Why are we using data from this group or this particular location?”

Students utilize Microsoft’s Excel, IBM’s SPSS, and Alteryx Designer for their course work and project. Alteryx is a sophisticated, full-spectrum data science platform utilized by industry leaders like Harley Davidson Motor Cycles, Deloitte, Alaska Airlines, Chic-fil-A, and Toyota.

The statistical methods course (DSC 503) builds on the foundation of the introductory course to give our students solid quantitative skills, one of the three key components of a data scientist. Using IBM’s SPSS software, the key goal of Statistical Methods is to understand which statistical tool to use and why. It is important to have this statistical understanding because a data scientist on a team could be the person with the most statistical training or, on the other extreme, the only non-mathematician who has to be able to effectively engage with the mathematical gurus (i.e., Quants).

After these two foundational courses, students then dive deeper into data science with our “hard-core” data science courses: Data Mining (DSC 607) and Machine Learning (DSC 609).

The Data Mining course utilizes R and Alteryx Designer to learn and apply complex data analysis techniques like k-nearest neighbors and artificial neural network classification techniques as well as cluster analysis using supervised and unsupervised learning. Just like with statistics, it is important for students to learn when to use each tool and why.

Machine Learning continues where Data Mining left off and expands the data science techniques with random forest, support vector machine (SVM), and deep learning. This course introduces students to Python programming and continues data analysis with Alteryx Designer.

After the completion of the first four core courses, students take 12 credit hours of electives in any discipline they choose. This provides the third component of a strong data scientist: domain knowledge. Students can chose to take the specified specialization courses in Business Analytics, Social Science Analytics, Cybersecurity, or Financial Crime, or students can opt to take any graduate courses that best support their academic and professional goals.

After completing their electives, students take the final two data science courses: Data Visualization and a Capstone, either a project or thesis. Data Visualization (DSC 611) is a crucial skill. As I tell all my students early and often, if you do the best data science investigative work in the world but cannot tell the story, paint the picture, or persuade decision makers with your work then the value you add to an organization approaches zero. Data visualization and effective communication are key to being a successful data scientist; students expand their use of Alteryx Designer and begin to use Tableau software.

As I tell all my students early and often, if you do the best data science investigative work in the world but cannot tell the story, paint the picture, or persuade decision makers with your work then the value you add to an organization approaches zero.

Last, students complete a capstone project or thesis: DSC 680 or DSC 690, respectively. The capstone project or thesis uses the data science investigative process applied toward a problem or research hypothesis. The goal is to show mastery of the program’s goals while showing knowledge gained from the elective courses. The capstone, be it project or thesis, becomes the hallmark of your graduate experience; it is an exciting endeavor.

[] How are the different specializations integrated into the MSDS program curriculum and what advice do you give to students regarding their choice of a specialization?

[Dr. McCarthy] When students come to me to discuss elective courses, I mostly listen and then advise them toward the specialization they already told me they are the most excited about. Often, when a student wants to try more than one specialization, they are relieved to find they can take elective courses from both; they give up the option to earn a specific specialization but gain the domain knowledge that is customized to their unique goals.

When a student is less clear about what they want, I generally steer them toward Social Science Analytics or Business Analytics courses because these courses apply more broadly to many different professions. By contrast, Cybersecurity and Financial Crime Specializations are in high demand but both are narrower in focus.

Specializations are fun and can really help students learn a lot about a new domain. That said, tailoring the elective courses to align with an individual’s personal and professional goals is often the best choice.

[] For students who are unsure if an online program is right for them, what are some of the pros and cons of pursuing a master’s in data science or data analytics online? What type of academic, technical, and/or career support services does Utica College provide to students in the online program?

[Dr. McCarthy] An online program has benefits and challenges, like any program. The top benefit is the high-quality education delivered when you need it. Few working professionals can take 18 to 24 months off from work to earn a master’s degree. Likewise, many people do not live near a college or university. An online program provides the opportunity for people who otherwise could not earn a degree due to time or location constraints.

The workload goal for each course is typically 15-20 hours for an average week. This is a lot of work but generally manageable for most students. Faculty are also available for questions or huddles throughout the week, not just during office hours. Utica College has great online support; there is 24/7 technical support with actual people able to work through and solve technical issues. From time to time, I use this team to help me with technical issues with the Engage platform and they do a great job.

Utica College has a program called “Smarthinking” to help students with their papers. Students who utilize Smarthinking turn their paper in and get timely feedback on the structure, formatting, and grammar. Smarthinking also supports resume and cover letter reviews.

Students and faculty in the program can join the Utica College Data Science Community group on LinkedIn. This group shares jobs, industry information, and new ideas in the data science discipline.

Online students are able to participate in career counseling appointments with Utica College’s Career Services team, usually over the phone but they can Skype if needed. You can receive resume and cover letter reviews, job search and interviewing strategies, LinkedIn reviews and usage strategies, among other general support and encouragement. There are other online resources that students may take advantage of including application material and interviewing guides, software for resume development and video interviewing (Optimal), company research databases, career exploration and salary tools, and more.

[] What attributes do you look for in applicants to the online MSDS program, and what advice would you give to potential applicants in terms of submitting a competitive application?

[Dr. McCarthy] In general, students who show curiosity and persistence will be very successful in graduate school and this data science program. Students need drive to solve problems and the persistence to stick through the difficulties because most solutions are not straightforward. Curiosity is easily seen when students take other courses or boot camps to hone their skills. Applicants who discuss how they strive for continuous learning and improvement in their application essay showcase that they have the curiosity and persistence needed to be successful in an online data science graduate program.

[] Data science is an evolving field, and there are a growing number of online master’s in data science programs. What are some of the unique features of the Utica College program and what advantages does it provide students from a career training perspective?

[Dr. McCarthy] The discipline of data science is moving at a million miles an hour and it is important to stay current. We do this in several ways. First, our advisory board will help us stay current with industry trends to help update the curriculum. Second, staying connected with our graduates as they go forth into industry as data scientists also helps us stay connected to the field. After you graduate, be ready to engage with us to keep the MSDS program up to date.

The discipline of data science is moving at a million miles an hour and it is important to stay current. We do this in several ways. First, our advisory board will help us stay current with industry trends to help update the curriculum. Second, staying connected with our graduates as they go forth into industry as data scientists also helps us stay connected to the field. After you graduate, be ready to engage with us to keep the MSDS program up to date.

Utica College’s MSDS is unique among other data science program for several reasons. First, the MSDS program is in the Sociology Department as opposed to other programs that house their program in a computer science, math, or business school. This seemingly subtle difference is very important; students receive a very unique social-science perspective woven throughout the program. The social-science mindset is different from an engineering mindset fostered in other programs in the computer science or math departments. CS and math are important; they are main components that make a great data scientist. But the social-science focus really sets Utica College apart because it provides a foundation to better understand the context of the data, the analysis, and the people affected. Utica College students have an advantage because they receive the technical skills taught everywhere but they really learn to be, what I call, “data thinkers.” A data thinker is someone who understands that context is perhaps as important as the data. Utica’s social-science focus is crucial to understanding the complex issues that face most organizations utilizing machine learning algorithms.

Second, our class sizes are small. The maximum class size a student should experience is about 25 students. This enables faculty to really engage with students and work with each.

Third, you receive mentoring from the program director. During the first weeks of the program, each student meets with me, as the program director, to help understand your goals, customize the electives you need to achieve your goals, and prepare you for the capstone that will be your culminating experience for the MSDS. Additionally, a student success coach helps you enroll each semester and answers any questions you have about the program.

Lastly, our students and our graduates make our program strong. Our students provide feedback to make our instruction better and our graduates let us know how advances change the data science industry. We take continuous improvement very seriously in the MSDS program. There are countless updates and improvements made to our instruction based on the great feedback from our students.

[] Is there anything else you feel that prospective applicants should know about Utica College’s online MSDS program?

Many students worry about which data science software they will use in the program. This feels like a legitimate concern because most job listings request that applicants have training in certain software. This is important but it is also important to realize that there are dozens of software platforms and it is impossible to know them all. The important aspect is that you have experience with a sophisticated platform or two and balance this with open source packages. Utica College’s MSDS utilizes IBM’s SPSS, Alteryx Designer, and Tableau (three platforms) and utilizes two open-source programming languages: R and Python.

I use a personal story when I explain to students the importance of understanding how to think in computer languages rather than having a deep understanding of a specific programming language. When I learned programming as a graduate student, I learned the syntax language for SAS, the proprietary software licensed by my university. I felt great about my SAS programming skills but my first company after graduate school did not use SAS. Rather they utilized a very specialized software package and then shifted to a totally different software shortly after I learned the first. I used none of my SAS know-how but I did use my understanding gained from my SAS coding to enable me to pick up SQL programming pretty quickly as well as the other two new software packages.

This ties back to important attributes I mentioned earlier: curiosity and persistence. I had to use my curiosity to help find the solution with the new software and persistence when the answers were not easy to find.

Finally, I want students to know that this program is rigorous. You will learn a ton but it is up to you to do the work.

Visit Utica College’s website to learn more about the online Master of Science in Data Science program.