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Meet Soorej: A Residential On-Campus MS-DS student who chose to become a Student again after 4.5 Years in Industry.

When Soorej decided to pursue a master’s degree, he was already a Senior Data Scientist with 4.5 years of experience at XPO.

He had worked across different projects, helped hire new team members, and developed a particular interest in finding problems hiding inside systems that otherwise seemed “normal.”

But the field around him was changing.

“I started with classical machine learning problems at XPO. We saw more and more problem statements and with new statements I wanted to try computer vision and natural language programming projects and eventually, I started getting into LLMs.”

It’s that progression that eventually brought him back to school.
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Keeping up with a field that keeps moving

Soorej’s approach to solving problems has not changed much since coming to ���Ҵ�ý�ƽ������. He starts by seeing what others have tried, reviews current research and then decides how he wants to approach the problem. What��has changed is what he has the opportunity to explore.

“I’m still learning more about computer vision and vision language models through my courses and with everything going on in the data science industry. It’s a fast-changing industry, and staying up-to-date can be hard. You have to be active in learning.”

One of his most challenging experiences has been CSCI 7000, Vision Language Models in Robotics.

“There were many real-world projects where we used new approaches. It was a heavy workload, but you learn what is happening right��now in the industry.”

Computer vision particularly appeals to him because of the problem solving involved.

“There are multiple layers to it — colors, edges, and it’s a lot harder for computers to put it together. It’s sort of like solving a puzzle.”

Starting over without starting from zero

Returning to a university after years of full-time work was still an adjustment.

“I wasn’t used to sitting in a classroom and listening to lectures anymore.”

But Soorej did not leave his professional experience behind when he became a student.

During his first year, he became involved with the Data Science Student Association (DaSSA) and served as Professional Development Chair. At the MS-DS Hackathon, he helped teams think through their approaches and troubleshoot coding problems.

“My industry experience was really helpful.”

The event also gave him something different from his previous professional experience: the chance to watch many teams experiment at once.

“There were so many projects people were working on. So many new things people were trying. Hearing people say, ‘Oh — what are they doing? We should do that,’ was fun.”

Why Boulder?

Soorej was admitted to three institutions before choosing ���Ҵ�ý�ƽ������.��

Part of the decision was academic:��

“The program and the courses seemed interesting, and the freedom to choose electives was interesting.”

Part of it was simply Boulder.

“I saw a video of Pearl Street and the campus, and I knew I wanted to go here. It was like something out of a movie.”

After years in industry, he wanted the experience of being a student again too. His first months included new people, hikes and campus events alongside coursework. His advice?

“...Be open to it, and say yes to every plan.”

Take the hard path

Soorej’s advice for someone considering graduate school reflects the way he has approached his own experience.

“There’s an easy and a hard way to finish each course. You can take the courses, have a good GPA and leave your Master’s. But you could take some courses that might feel like a struggle, and even if you lose a few grade points you’ll learn something.”

For someone who had already built a career in data science, returning to school created an opportunity not to repeat what he already knew, but to deliberately move toward what he did not.

His advice?

“Take the hard path, it’ll be fine.”