As one of the first graduates of Bryant University's Master of Science in Data Science program (MSDS), Agustin Suarez ’24MSDS learned a lot about programming, machine learning, and artificial intelligence (AI).  

Equally important is what he discovered about himself. 

“The most valuable thing for me during college was understanding how I learn best,” says Suarez, who joined Google as a software engineer shortly after graduation. “You can learn a lot about software engineering during your college years, but at companies like Google, there are so many internal tools, and there’s just no way of learning them from the outside.  

“What you learn in school is a great stepping stone to learning on the job, and knowing how you learn is a great skill to have.” 

At Google, Suarez works on a sub-product of Google Ads called Funding Choices. “When publishers sign up for Funding Choices, we provide solutions to easily navigate regulations and also to monetize their website by showing ads,” he explains. 

“My day-to-day is hardcore software engineering,” says Suarez, who is constantly improving his technical and soft skills. “I'm writing code, fixing bugs, and creating new features for our product, which is the spine for a lot of different businesses.” 

Suarez also helps ensure that businesses using Google ads comply with data privacy laws, which vary from country to country. “We provide software infrastructure for websites to make sure that they adhere to the correct data privacy policies, that the user is protected, and that the company is also protected from being exposed to lawsuits,” he says. 

The work may be digital, but there’s a decidedly analog aspect to how Suarez processes the information needed to do his job. 

“When I listen to things, I remember the highlights; when I see things, same thing. However, when I write things down ... I am able to actually understand things, especially when it comes to software engineering and complicated programming rules.” 

“When I listen to things, I remember the highlights; when I see things, same thing,” he recalls from his Bryant classroom experience. “However, when I write things down  — not on the computer, but by hand, pencil and paper  — I am able to actually understand things, especially when it comes to software engineering and complicated programming rules.” 

It's a learning style that Suarez says his Bryant professors were happy to accommodate.  

“They are flexible for you to learn on your own terms,” he says. “Most of them did draft or draw out examples for me. Pencil and paper may take longer than typing, but the bottom line for me is it’s more efficient than watching the same video five times.” 

Suarez’s time at Google has changed his perspective about how software products are developed, including the importance of teamwork. For example, he says, developing a product like Google’s AI tool, Gemini, involved far more collaboration than he had envisioned. 

 “I’m on a team of 30 people, and all of us are committed to one small product in the Google environment,” he says. “And these 30 people are part of another group that has another three teams that have 30 people each. And that team is part of another bigger thing. The size of the actual work is just incredible.” 

Bryant’s MSDS program helped prepare him to work collaboratively, says Suarez – something he found especially valuable as he juggled his classwork with playing varsity tennis for the Bulldogs while getting his Master’s degree. 

“There are people from all areas of expertise – whether it be computer science, engineering, or mathematics,” he says. "Figuring out how to work as a group while having different backgrounds was a challenge. But the group work incentivized at Bryant was great and helped me a lot. My classmates were open and willing to help me with things that I struggled with.” 

 “Figuring out how to work as a group while having different backgrounds was a challenge. But the group work incentivized at Bryant was great and helped me a lot. My classmates were open and willing to help me with things that I struggled with.” 

Overall, Bryant’s MSDS program “was crucial for me to get a better and more in-depth understanding of technology like machine learning and to incentivize myself to learn more about the current tech ecosystem,” says Suarez. “Having a Master's on your CV increases your credibility, and in Bryant’s MSDS program you gain a lot of exposure to real-life projects and an understanding of how the industry uses the concepts that you learn during college.”  

For a class project, for example, Suarez developed a machine learning model to help AAA of Southern New England analyze their customer data. “It was nice for an actual company to give us a real data set to work on,” he says. “You get a real-life scenario, but you don’t have the pressure of performing to a real job’s benchmarks. There was a lot of wiggle room in terms of just exploring the data and understanding how the business operates.” 

Suarez’s career goals include “leveraging technology to make a meaningful impact in the overall economy, enhance efficiency, and drive positive change,” which he already sees happening with his work at Google.  

“The most exciting thing for me is knowing that everything I work on here touches the lives of millions, if not billions of people,” he says. “Knowing that the work I’m doing helps improve the lives of a lot of people is exciting. I’m at the forefront of technological development here.”