In Fall 2016, Capture Higher Ed data scientists, Dr. Thom Golden and Dr. Brad Weiner, debuted The Weightlist Podcast, a show dedicated to data science, higher education, enrollment management and machine learning … with a little beer and music thrown in for good measure. More than 15 episodes later, the podcast has become essential listening for professionals interested in new ideas and technologies, and how they may be applied to the business of higher education.
During the inaugural episode of The Weightlist, “Begin At The Beginning,” the two data scientists engaged in a little professional self-analysis. Exactly what is a data scientist anyway?
“Brad, you’re a data scientist,” Thom starts. “You go to parties … When people ask what you do, what do you tell them?”
Brad begins by saying that he’s basically a statistician, but data science and data scientists are newer terms that we are hearing more and more in popular and technical media.
“A data scientist is someone who wants to look at a difficult problem, or ask a difficult question, like any scientist would, and then try and develop meaning or answers using quantitative data,” Brad says.
Lower Barrier of Entry
While he’s reluctant to use the term “Golden Age” (because that implies that things are going to “become less good”), Brad says it’s a great time to be a data scientist.
“We’re in a tremendous age now where there are enormous data sets,” he says. “There is incredibly easy access to really good data sets. The barrier for entry is much lower, or easier to get through now, because you have all these opportunities to ask interesting questions about the world and have great data to dig into.”
The simplest way to understand about what a data scientist is: “Think of a lab scientist, and then think of the lab as simply a bunch of data sets,” Brad says. Or there’s the joke, “a data scientist is just a data analyst with a Macintosh.”
Thom adds: “I’ve also heard it described that a data scientist is a better programmer than most statisticians. And a better statistician than most programmers.”
A Hacker Mentality
A key characteristic of a data scientist, according to Brad, is “a kind of hacker mentality — that it doesn’t matter what tool you use, it doesn’t matter what technique you use, as long as it’s supported and useful.”
The only barriers to coming up with the right answer are methodological or computational challenges, and your own imagination, he adds. “So a lot of times we program or hack our way to creative or innovative solutions, and sometimes we use statistics in a fairly robust way that a programmer or computer scientist might not.”
Data science takes massive amounts of flowing data sets, Thom says, combines it with machine learning and the latest technology. “It’s been revolutionary in fields like law, medicine, business and, of course, if you have Netflix or any kind of aspect of the web — Amazon, Google — you’re experiencing data science, and you’re experiencing machine learning.”
What Capture does is explore new ways of using data science within higher education, Thom says. “The field we love; the field we feel is uniquely tied to the missions of preserving knowledge, preserving humanity.
“It’s something we’re real excited about.”
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By Kevin Hyde, Senior Content Writer, Capture Higher Ed