SaiKumarReddy Pochireddygari remembers the moment he became interested in machine learning. It was 2015, and he had booked a $10 Uber ride to visit his uncle. Due to long wait times, he canceled the ride and rebooked a few minutes later only to find the fare had increased to $13. 

“This dynamic fare pricing mechanism intrigued me,” he said. “Curious about the sudden fare change, I discussed it with my dad’s friend who worked at Uber. He introduced me to machine learning and explained the underlying principles that caused the price fluctuation. This encounter sparked my interest in data and machine learning, leading to a deep passion for machine learning systems, particularly in engineering and operations.”

That passion eventually led Pochireddygari to Syracuse University’s School of Information Studies, where he graduated this year with a master’s degree in applied data science. He now works as a Senior Machine Learning Engineer with ADP and recently started working on building GenAI Ops and LLM (Large Language Model) Ops platforms from the ground up. 

“Although I have only been with ADP for a little while, I have already seen the immense technological advancements and applications of GenAI in HR and payroll software,” he said. “The exposure and learning have been unprecedented, and I am excited about the opportunities ahead.”

Pochireddygari has come a long way in his education and life. Originally from Peddapasupula, a small village in India, he remembers his childhood being challenging. 

“My father had to travel 5 miles to get us drinking water. I spent my childhood helping my family and going to school in the village,” he said. “Once modernization began around 2007, I moved to a town for my schooling and college education. After gaining some work experience and supporting my family, I came to study at Syracuse University.”

Pochireddygari chose Syracuse after extensively researching the school online and seeing the high-ranking Information Systems program and a strong data science curriculum. He was also impressed by the extensive and supportive alumni network, which was a significant factor in his decision.

“Once at Syracuse, my journey was transformative,” he said. “In my first semester, I had the opportunity to work with Jonathan Stromer Galley in the CCDS Lab as a research assistant, which I continued until my graduation. This experience exposed me to research and allowed me to contribute to various projects in the lab, learning new ways to approach problems.”

He also worked with Professor Joshua Introne on a data scraping ETL (extract, transform, load) project, which helped him gain valuable automation skills, and as a researcher and team lead in the Nexis Student Technology Lab. 

“The coursework in machine learning and big data at Syracuse prepared me well for both theoretical and practical aspects of machine learning, for which I am incredibly grateful,” he said. 

One school project that was especially meaningful to him was the Fraud Transaction Anomaly Detection project he completed his last semester. As part of the project, he developed a robust model to predict fraudulent activities in financial transactions. 

“By engineering 17 pivotal features, I significantly improved the detection capabilities, resulting in a 17% improvement in the F1 Score for fraud detection. The model was deployed on AWS (Amazon Web Services), ensuring scalability and reliability,” he said. 

“This project combined my expertise in statistical modeling, feature engineering, and cloud deployment, showcasing my ability to deliver high-impact solutions in a real-world setting,” he added. “It reinforced my passion for leveraging data science and machine learning to solve critical problems and make a tangible difference.

Now working as a professional in the field, Pochireddygari’s goal is to become an engineering leader in the field of machine learning. 

“Personally, I live by a simple motto: to improve myself day by day and keep moving forward,” he said. “I believe in continuous growth and development, striving to become better each day.”