Episode 53: Everyone Should Be a Data Scientist

Episode 53: Everyone Should Be a Data Scientist

Date of Publication/发布日期
November 12, 2021
Curtis Westbay
Files & media
Volume 2 2021-2022

There's a lot of talk about "21st Century skills"

But what are they? People educated in the 20th Century might bristle at some of the implications of a list of 21st Century skills: creativity, collaboration, independence, research skill. Weren't these things valued in pre-internet times? Maybe it's just that there is a greater emphasis on these sort of skills that are needed in a more fluid, dynamic workplace. The types of 21st Century workplaces where the concept of an office with four walls and a tightly-woven team have given way to more and more remote workers and technology-forward working communities obviously need independent, self-initiated members. But who is to say that these competencies are anything new?

One area, however, where I've found a true transformation in the expected skillset from this new century is in data analytics. As a Classicist (a scholar of Latin and ancient Greek languages and culture), I am about as far away from modern times as I could be, academically. And yet, one of the first things I did this year as I prepared to teach an elective Latin course was a data study. I took Vergil's Aeneid, the canonical work of Roman myth, and worked with a PDF to break down the vocabulary contained therein. From here, I could prioritize the vocabulary that would set students on a path to success, should they sit the AP Latin exam in the years after this introductory course. Data helps with planning, even if you're looking at things from 2,000 years ago.

But I just moonlight as a Latin teacher. In the college admission office, we have to be driven by data. Elsewise, our "expertise" is based on speculation, on some slapdash extrapolation of single instances of anecdotal evidence in student applications. So what if one student gets into a highly-selective school with a certain intended major with a certain score? Over time, we can look at the broader trends in the context of the data that surrounds a single variable. In this way, data analysis isn't an exercise in cherry-picking (finding data to fit your hypothesis). Data should drive decision making.

I'm not advocating that all of our students sign up for AP Statistics (though, Mr. Mahoma might!). I am more or less saying that quantitative reasoning skills are more important to employers than ever, ergo more important to colleges... ergo more important to you. Who could have predicted that I would write a thesis in college on Pliny's Naturalis Historia... and now I spend more time with spreadsheets than scansion? Another key distinction between 20th and 21st Century labor markets is just how much more transient employment has become. People commonly transition between jobs and even between careers several times in their adult lives. Awash in volumes of data, businesses rely on all of their employees to be data scientists. Data allows for objectivity in business practice, regardless of the composition of a team.

Students don't have to be statisticians or mathematical savants to be valuable in this new order of labor. They just have to develop strong quantitative reasoning skills. I definitely didn't hold onto every lesson I learned in math classes (what is the chain rule? what is a parametric equation?). Those lessons will be important to some, but they haven't been important to me. Nevertheless, because of the skillset that I developed in high school and college, I can find statistical approaches to answering questions that affect our students. Companies align their divisional priorities around central data-driven goals. Data is a common language for an organization.

So, whether you, like me, care more about language or art, or you're a hardcore STEM student all the way, everyone should be a data scientist. Data analysis is a 21st Century skill (whatever that means) that even a scholar of dead languages will probably need.