Alum Feature

MSDS Alum Uses Program Knowledge to Communicate Data Science to Audiences

December 15, 2020


For Gabriel Rushin, MSDS 2017 alum, data science is about going deeper into how machine learning models work and communicating those results to broad audiences. 

Rushin currently works as a Senior Machine Learning Engineer Manager at Procter & Gamble in Cincinnati, Ohio. 

Rushin completed his undergraduate studies at the University of Virginia, where he majored in Mathematics, with a concentration in Probability and Statistics. However, he explained that math was not the original path he intended to take. 

“I entered college as a pre-med student but realized that I didn't want to continue the pre-med track after finishing my prerequisite courses. After that, I ended up committing to math.” 

Rushin enjoyed the math classes, and from there, took a few coding classes during his undergraduate career. He explained how those classes piqued his current career interest.

“Once I took coding classes, I became interested in combining math and coding, so that's how I ended up in data science.” 

During his fourth year at UVA, Rushin applied to the MSDS program and was accepted to the Data Science Institute (now the School of Data Science). Upon graduating in May of 2016 with his Bachelor’s Degree in Mathematics, he began the master's program. 

Reflecting on his time at the School of Data Science, Rushin noted that the most valuable parts of his MSDS experience were learning how to lead effective presentations and learning how to be comfortable with presenting projects frequently.

“There were a lot of presentations in the program, and I know some people don't want to do them, but that's what work is focused on. In a lot of jobs, you're eventually going to present, and make sure that your presentation is compelling to your target audience,” Rushin said.

Additionally, the capstone project was an impactful part of Rushin’s education at the School of Data Science. 

For his capstone project, Rushin worked on a team for Capital One, to compare the predictive power of banks’ fraud protection models. For current and incoming MSDS students, Rushin advised them to lean into the capstone experience, as it has the potential to impact job interviews and future career interests.

“Utilize your Capstone,” Rushin said. “Capstone projects are opportunities for you to deliver valuable, quantifiable results that you can use as a testimony of your long-term project success to the company you work for and other companies in future interviews.” 

Rushin landed his first job as an Associate Data Science Manager at P&G right after graduating from the School of Data Science in May of 2017. Since his arrival, Rushin has explored various roles at P&G. 

In his first position, as an Associate Data Science Manager, Rushin worked within the Central IT Group. He noted that he was a part of a small team when he started this role, however; this group has grown significantly in his time at P&G which shows the growing demand for data science.

“After my first position, I moved on to a new role within beauty,” Rushin said. “I was working with brands like Old Spice, Olay, and Head & Shoulders where I executed data science work, involving geolocation targeting.” 

Geolocation targeting refers to marketing different advertisements to consumers within the beauty industry based on location.

Rushin also describes how revisiting a familiar part of the company in a new role can help propel productivity.

“I’ve recently gone back to the Central IT Group in a Senior Machine Learning Engineer role, where I facilitate computer algorithm expansion with the data science team to result in more scalable sets within the query pool,” Rushin noted.

Of his various positions at P&G, his favorite was working within beauty. 

“My experience in beauty taught me how people outside of data science view data science and how to communicate my findings to the business,” he explained.

Specifically, Rushin worked with business leaders in the beauty industry, which involved breaking down the data science behind marketing products.

“It's not something that just magically occurs like a genie in a bottle, it's an actual process that you need to bring your audience along in.”

Throughout his work at P&G, Rushin has grown increasingly interested in building machine learning models. 

This interest led to his enrollment in a part-time computer science master's program at the Georgia Institute of Technology in 2019 that Rushin is currently pursuing alongside his full-time work. 

“I'm majoring in computer science with a specialization in computing systems,” Rushin explained. “The purpose of this degree is to combine it with my data science degree to build data-driven machine learning applications that can be utilized throughout P&G.”