How Jay Sueno Took on New Data Science Skills to Land a Role at Amazon

In many ways, Jay Sueno started as a self-taught data scientist. He spent countless hours coming up with his own methods of visualizing and reporting critical data at MamaP, the company he co-founded to sell eco-friendly alternatives to everyday products. But when a friend told him about a data science boot camp, he became curious and started doing some research.
“I was really fascinated with machine learning and artificial intelligence, and I wanted to dive into that,” said Jay. “My friend had taken a data science boot camp before entering grad school, and she spoke very highly of it. I felt really motivated to learn a new skill set.”
Jay enrolled in the Data Science and Visualization Boot Camp at UC San Diego Extension. It was an exciting opportunity — and a huge life change.
Making big changes happen
“I was 40 years old when I joined the course, and it was the first formal schooling I’d experienced since my undergraduate years,” said Jay. “Gaining the skills relevant to today’s workplaces required learning a whole new way of thinking, so it was a bit of a challenge getting up to speed.”
Starting the boot camp, Jay worked hard to keep up with the material. “It was like drinking from the fire hose,” he said. “It challenged me on so many different levels.”
But the swift pace of the boot camp kept Jay engaged. In addition to the core curriculum, he found that the program provided plenty of resources to support his success, even in the remote setting.
A full-time instructor and collaborative group of classmates empowered Jay and his cohort to lean on each other, bouncing ideas around and grouping up on projects. All in all, the course structure encouraged Jay to keep going — and the team-oriented environment was something he had specifically prioritized in his program search.
Finding a groove to keep up
To facilitate the successful completion of his daily boot camp responsibilities, Jay found a rhythm that suited him and fit in with his existing responsibilities.
“On boot camp days, I would quit working on MamaP tasks at around 4:00 or 4:30 p.m. to leave time to work on my assignments. A couple hours later, class would start, and I would stay until the very end of office hours so I could talk through any ideas and questions I had,” said Jay.
By the time he would finish, it would be late at night. It was quite the commitment, but Jay knows that making the most of his time at the boot camp was critical to his success.
One of Jay’s favorite group projects was called “Machine Learning Predictor: Trump’s Tweet & The S&P500.” The project employed a machine learning algorithm using tweets from the former U.S. President to make predictions about the stock market.
“The program would create sentiment scores for ten years’ worth of tweets,” said Jay. “Then we would filter for certain keywords, such as ‘stock market bull run’ or ‘bear market Wall Street,’ isolating them to analyze stock market trends in relation to the tweets.”
While technically challenging, Jay and his teammates pulled it off. “We actually managed to get the program to something like 60% accuracy,” he revealed.
Pivoting to start something new
While a large source of motivation for Jay in joining the boot camp was to empower MamaP’s data science and analytics, he was also thinking about how these hard-learned skills could enrich his future career. Ultimately, that’s what led him to his current role as a Data Analyst II at Amazon.
“I job hunted for about two and a half months after completing the boot camp,” said Jay. “There were a lot of dead ends because there’s so much competition out there, but I didn’t give up.”
“I started following and interacting with some YouTube influencers in the data science space,” said Jay. “One of them recommended that I appear as a guest on an episode of a podcast called How to Get an Analytics Job. They were looking for someone with a good resume and LinkedIn profile that they could ask about and dissect, and thought I might be a good fit.”
Opening new doors
Appearing on the podcast opened many doors for Jay, but by that point he had already networked with recruiters at Amazon and received an offer. Not long after, he reappeared on the podcast to talk about his big Amazon win.
Of course, many of Jay’s responsibilities for a company as big as Amazon are confidential, but he was willing to shed a bit of light on his current day-to-day.
“I’m doing financial analysis, so I’m working a lot with technology like Pandas and Python, and doing project management,” said Jay. “We’ll be getting into some SQL work soon, but primarily it’s Excel with Python and developing insights based on those analytics.”
Jay emphasized that achieving success beyond the boot camp requires a significant degree of personal investment: “It’s really up to you to look for the opportunities, network, and leverage your previous experience and social media platforms like LinkedIn to get you into a company like Amazon. I also highly recommend using your boot camp career advisor throughout your job search. Mine was almost like a therapist to me during the interview process. I really think that was instrumental in me landing where I am now.”
Interested in a career in data science? Explore UC San Diego Extension Boot Camps and start working toward a career in tech.