Data Science Institute intersects with business industry

Efforts to understand the applications of data science in the business industry from students, professors, and industry partners

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With data science requiring experience in realms including computer science, algorithm and model development, data extrapolation and statistics, classes may tend to prioritize technical topics.

Maddy Sita and Tyra Krehbiel | Cavalier Daily

In acknowledgment of the importance of analytical skills in the context of business, the University’s Data Science Institute and the Darden School of Business started a dual Masters program in Business Administration and Masters of Science in Data Science degree program in 2017. The two entities have maintained and strengthened their connections as data science and data analytics become increasingly ubiquitous in a variety of fields and will continue to do so with the creation of the University’s School of Data Science.

With plans for the University’s newest school underway, the DSI has placed an even greater emphasis on engaging business partners in Charlottesville. In a talk hosted by the DSI on Friday, Jan. 25, entitled The Future is Now: How AI and Machine Learning are Shaping the Market, Nate Haskins, Standard & Poor’s global chief data officer,  and DSI Director Phil Bourne discussed the applications of big data in the private sector and the progression of job titles and technology. 

Data science largely entails collecting, analyzing and interpreting data in the context of different domains, from the worlds of investing or marketing and advertising to that of health care. As such, Bourne and Haskins touched on some of the skills that future data scientists should learn in the classroom before entering a diverse and evolving workforce. 

With data science requiring experience in realms including computer science, algorithm and model development, data extrapolation and statistics, classes may tend to prioritize technical topics. Yet, both Bourne and Haskins mentioned the value of being well-versed not only in traditional technical skills but also those acquired in different areas of study.

“[In school], I found those other courses that were helping me flex other muscles in my brain and understand new things that I hadn’t been exposed to before — that was just was a need at the time,” Haskins said. “It helped me later on when I came back to in my business career things that were more related to technology and those kinds of things that the well-rounded nature was there.”

MSDS graduate student Catherine Beazley echoed the need to combine a foundation in data science skills since a large number of companies and positions often require that employees have some experience with machine learning and an ability to understand the context in which data science projects are conducted.

“I think it will be important to be very versatile,” Beazley said. “I’ll have a toolbox of data science skills, and then I’ll have to be able to pick up domain knowledge and apply those skills to whatever field I’m working in.”

Haskins and Bourne then extended the need for an interdisciplinary approach to the business world. Specifically, Haskins mentioned that having a distributed, wide-reaching approach to data science throughout S&P Global was essential to have an edge in the marketplace, particularly since data scientists can often apply innovative data science techniques to solve seemingly unrelated problems.

“Those data scientists understand the art of the possible,” Haskins said. “They will bring ideas to that table that are not coming from the business because they might be able to draw on experiences or something they’ve contributed to that might be in a completely different field.”

Conversations with students after the event demonstrated their willingness to embrace the principle of diverse education and experiences. Winfred Hills Jr., a graduate student in the dual MBA and MSDS program, has worked in the past as an IT Business Analyst at Ernst and Young LLP, where he realized that data science skills were fast becoming powerful tools in the business world.

“We had numerous education classes to keep us abreast of what was going on in the industry,” Hills said. “A lot of them focused around using Python and R and the applications of that in business. When I saw all of the potential ways we could use these to influence the client, I knew for the business leaders of tomorrow it would be essential to have these skills.”

Other programs and services that the DSI offers include career counseling and professional development. Reggie Leonard, the associate director for career connections and community engagement, actively works with students to help them think about what jobs interest them and understand the opportunities available to them.

“Students are curious about the general landscape where analytics can be used,” Leonard said. “It’s one of those things where a lot of people use these big statements like ‘Everyone is analytics, you can go anywhere and work in data science,’ but everyone and anywhere doesn’t mean anything if you don’t know where to start, so I’m helping to operationalize those words for students in the context of what their interests are.”

When discussing options in the business world with students, Leonard emphasized keeping an open mind about the range of possibilities that exist, as well as the places in which opportunities might arise. With the hotbeds of data science being in cities such as San Francisco and New York, not as many DSI students remain in Charlottesville after graduation. 

However, according to Leonard, there is a data science and machine learning culture in Charlottesville, and with the new School of Data Science, the presence of these fields in Charlottesville will only continue to grow. There is generally a fair number of graduates that work at Charlottesville companies including CCRi, Elder Research, S&P Global, CounterFlow AI and WillowTree. The DSI will also continue to engage with the Charlottesville data science community on a regular basis by holding DSI-sponsored events and workshops in conjunction with local businesses, as well as a career week open to first-year data science graduate students before classes begin.

“I work so closely with the students that I know what they are interested in, what kinds of questions they have for employers, what kind of hesitations or even misconceptions they have about employers, and I am able to relay those directly to employer partners and help to bring them in to assuage those misconceptions and things like that through info sessions and technical talks,” Leonard said.

Now, as the University prepares for its new school of data science, Bourne said that it would be a “school without walls” that would continually interact with both the other schools at the University and Charlottesville as a whole. In fact, according to Bourne, there is the possibility that there could be representation from the private sector within the actual building once it is created in an effort to foster collaboration and the exchange of best practices.

“The dream is that [the exchange] helps drive the economy in the Commonwealth, and also that it brings the private sector closer to our students so that there is a direct relationship there,” Bourne said. “Our mantra is really in effect not to own anything but to be a part of everything.”

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