Beyond a career in machine learning and data science, Yemi Odeyemi (Ph.D. ’20) wanted an opportunity to lead. He got that chance and more as he jump-started his professional journey in Chapman University’s Ph.D. program in Computational and Data Sciences.
He quickly discovered that his professors in Schmid College of Science and Technology really meant it when they said that they value all voices and want students to realize their potential.
With their help, Odeyemi landed prominent internships and contributed to a handful of research projects that netted published results. In addition, one of his faculty mentors, Professor Hesham El-Askary, Ph.D., invited him to serve as an advisor on the Chapman Graduate Academic Council, to which he contributed ideas that influenced graduate education policies at the university.
“I learned a lot about how policies and decisions are made,” Odeyemi says. “That experience will help me as I work not just with data but also on planning and strategy in my professional life.”
After earning his Ph.D. earlier this year, Odeyemi considered multiple job offers before starting in June as an algorithm and data scientist with Beckman Coulter Diagnostics in Sacramento. There, he’s working to classify clinical microbes using machine learning tools and neural networks.
We asked Odeyemi to tell us more about how Chapman’s CADS Ph.D. program prepared him to succeed in his data science career.
What attracted you to the computational and data science graduate program at Chapman?
“After getting my master’s in biotechnology in Florida, I got a year of experience working as a data scientist for a small start-up, and I kind of felt inadequate. This field is still evolving, and I found that I needed to fill a gap in my expertise. I have a very strong biology background, and I wanted to link that to an understanding of working with large data sets. I was looking for a program that was very strong in AI, data science and machine learning, and I wanted to be in California because of all the biotech companies here.”
How did your academic experience translate to the professional skills you need?
“I learned about capturing data, but I also learned how to clean or massage the data – how you preprocess it so you get the right result. The modeling part is also very important. You set the mathematical algorithms so you can actually predict, based on pattern recognition. That’s where machine learning comes in, so it can predict based on learning over time.”
What’s the most important skill you learned in the Ph.D. in CADS program?
“First and foremost, leadership. Professor El-Askary helped me gain the confidence not to shy away from responsibility. A lot of us are used to looking from the outside. I learned it’s better to be on the inside looking out. How can you influence the outcome if you’re not part of the process?”
How would you summarize your Chapman experience?
“It was challenging, but I appreciated that the professors had open-door policies and always wanted to help. I added robust programming language skills, and I also learned about working with people from different backgrounds, whether it’s collaborating on research or learning from professional experience. I forged a lifetime of friendships with brilliant people who want me to succeed. These things I consider priceless.”
Learn more about Schmid College’s Ph.D. in Computational and Data Sciences program.
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