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New data science major meeting high workplace demand

Want the best job in America (other than pillow tester on the night shift)?

Become a data scientist. That’s according to Glassdoor’s 50 Best Jobs in America for 2018, as reported by Forbes magazine. The reason: A median base salary of $110,000 and 4,524 job openings nationwide.

Glassdoor based its rankings on median base salary, job openings and job satisfaction. Data scientist scored a 4.2 on a scale of 5, a mark topped by only two other occupations. And, of course, the task of producing these rankings was the work of a data scientist.

So it should come as no surprise that Kurt Cogswell, head of the Department of Mathematics and Statistics at South Dakota State University, is expecting big things from the data science major that was approved this summer by the South Dakota Board of Regents for SDSU. An associate degree also was approved then.

The department already had a master’s degree in data science and a math degree with a specialization in data science, which was new in spring semester.

While the major is new, the coursework already was in place and no new faculty needed to be hired for the major, Cogswell said.

Existing students first to jump on board

Emma Spors
Emma Spors

The approval came too late for the department to use it in recruiting the current freshman class, but it is attracting interest from current students.

Emma Spors, a sophomore from New London, Minnesota, discovered the major this summer after deciding that her original major of biotechnology wasn’t a good fit. Samuel Ivanecky, a senior from Farmington, Minn., decided to add data science to his existing math major. He also is pursuing minors in computer science and statistics.

Spors said, “I have always liked math. I really enjoy the feeling when you have completed a complicated problem correctly. Plus there’s lots of job opportunities in different sectors of business or the government.”

Ivanecky enrolled as an electrical engineering major but made the switch toward math and computer science. He had planned to add the data science specialization but after the regents’ action this summer he switched to a data science major because he already had scheduled the classes he would need to complete the major.

“I was taking a lot of extra math courses this year for personal interest—exploratory data analysis, predictive analysis, time series analysis,” Ivanecky said.

Variety of data science options

Cogswell said all those courses can be applied to the data science major. A bachelor’s degree requires 120 credit hours with 50 of them in the major requirement. For an associate degree, it’s 60 credit hours with 24 within the major requirement. The specialization for math majors, which can prepare students for the master’s in data science, requires 30 credits.

“The variety of data science degrees prepares students either for direct entry into the workforce or for entry into competitive graduate programs,” Cogswell said.

Neither Ivanecky nor Spors are ready to decide about graduate school. Ivanecky plans to test the job market first. He had a few introductory interviews, but will look more seriously after the first of the year.

Holding a bachelor’s degree in data science as opposed to a specialization, “shows there is more coursework emphasized in that area. There is a little bit more hands-on experience in school as opposed to waiting until an internship to get that,” Ivanecky said.

Extra credit: Cross country research

Samuel Ivanecky
Samuel Ivanecky

He said he has enjoyed “digging into data to discover trends and make predictions rather than just solving a problem. We take a less-guided approach (compared to statistics) and learn how to approach a data science problem on our own rather than following set steps in a typical class.”

Ivanecky has been applying his learning to personal interests, including cross country. The SDSU distance runner has been gathering data from key regular-season meets and comparing that to top finishes at the NCAA championship. He also figured in whether a team tends to run up through the pack or lead the pack, and then compare that to final results.

Given those interests, it’s not surprising that he would like to land an analytics position with a sports team or a shoe company.

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