Tyler Nelson, a data scientist in the strategic data solutions group at Apple Inc., is focused on the area of cybersecurity, working to build and maintain fraud programs for various business lines within the Apple ecosystem.
“Most of these programs use machine learning algorithms to detect and deflect fraud to help give our customers a better experience,” he says.
Nelson says he always wanted to use his head in math and statistics to solve real world problems, but he initially thought it would be in the pharmaceutical and medical fields.
“In my last year at Baylor, I started researching areas where my skills were applicable. I realized that data science would be a smooth transition, and it fit my skills and interests more,” he says.
Nelson daily confronts a new set of challenges which require him to think critically and creatively using data science and machine learning to solve problems. He says these skills were sharpened and encouraged in Baylor’s learning environment.
“Having a solid analytical and statistical foundation is essential to be a good data scientist,” he says. “Therefore, receiving a PhD in statistics made the transition almost seamless. The program at Baylor is quite applied when it comes to class work and research.”
Nelson, who earned a bachelor’s degree in mathematics and statistics from Colorado Mesa University in 2013, says at Baylor he was encouraged to apply his in-class learning to real-world problems through coding and simulation. He believes this distinguishes the University’s program.
“I was able to get very comfortable reading and writing code, which now I do on a daily basis,” he says. “Furthermore, our department is quite small, which made our classes feel more intimate and engaging. That is exactly what someone like me needed to
Nelson acknowledges that many people become wary when they hear about technological innovation such as AI and machine learning. However, he believes the ability to analyze and interpret data in previously impossible ways makes the world safer and healthier.
“Data is a powerful thing, and we as data scientists need to be aware of this and make sure it is being used properly,” Nelson says, adding that the ability to fully automate decisions gives the ability to answer more questions which lead to faster results. “I see data every day improve the response time and alert us of issues which allows our company to function more efficiently.”
Approaching issues in a moral and ethical manner is precisely what is needed in the world of data sciences, he says, something that Baylor is well equipped to instill in students. Nelson chose Baylor because, in his view, the faculty genuinely care about students’ success during college and beyond.
“Most of them, if not all, have a strong Christian foundation,” he says. “I don’t believe these two points are independent. They mold students into adults with great character and morals.”