Blog

Catherine Renner

Associate Data Scientist

Eric Roberts

Associate Data Scientist

Making Data Science Relevant to Teens: Predict Flavor-of-the-Day Sales!

Topics: STEM Outreach.

This past fall, Northwestern Mutual’s K-12 technology outreach program, hi, Tech, hosted the company’s first-ever Data Science Job Shadow event, in partnership with the Northwestern Mutual Data Science Institute. Seventy high school students were invited to attend the one-day event – 10 from each of seven schools across Milwaukee County – to learn about data science, what a data career might involve, and how it can be applied to business.

When Associate Data Scientists Catherine Renner and Eric Roberts were tapped as hosts, they knew they'd want to present information and structure activities in a way that would engage teenagers. The hook? Custard! The challenge: Based on actual past data from Culver’s restaurants, predict how much (in dollars) the flavors-of-the-day will sell next month.

Why use frozen custard to help teach data science?

Catherine: We tried to pick data sets that anybody could look at and understand. Most people don't know the ins and outs of insurance – especially kids – so our Northwestern Mutual data would likely be too difficult for them to wrap their heads around. We didn't want any students to feel left out if they didn't understand what we were talking about.

Eric: Plus, we didn't want to bore them to tears! We hoped something like a turtle sundae would grab their attention. Who doesn't love custard?

How did the job shadow event work?

Catherine: We split the students into groups of five and made sure no two students from the same school were in the same group, hoping they'd learn to work with people they didn't know. Each group was joined (and led) by a Northwestern Mutual employee whose job involves the use of data. Together, they worked through the activities of first understanding the data, then applying data science to reach new conclusions. It was awesome to see all the students interact with each other and ask questions – both about the project and careers in data science.

As you watched the activities unfold, what did you learn about the students?

Catherine: The kids worked through the activities a lot quicker than I expected. And they were astonishingly creative.

Eric: Some of the students had impressive backgrounds. From one school in particular, the students were already taking second-year college programming classes. They had well-informed questions about what data science was all about, and they were very curious about what plans they should be making to become a data scientist. You could tell they had already dipped their toes in the water a little bit, which I thought was very shocking – when I was in high school, I had no idea yet that I was going to become a data scientist.

I also learned something about the teachers: They're eager for tools that can help make this kind of learning relevant. A few of them came up to me directly and asked for copies of our materials so they could take the activities back to their classrooms for the rest of their students.

Why was it important for you to participate in the event?

Catherine: I wasn't introduced to data science in high school and had no idea what it was going into college. I'm grateful for the opportunity to expose data science to students and help them see how this can positively impact whatever they're looking to do in life.

Eric: I had amazing teachers in high school that made me fall in love with math and science – and I believe it is important to give back. I saw this job-shadow event as an opportunity to possibly change someone's life, just as my teachers changed mine. That might sound dramatic, but if even one student decides to alter his or her education and career goals as a result of this event, it could have a very large impact on their life.