Saumi Rahnamay

Prior to the UBC MDS Computational Linguistics program, Saumi was finishing his bachelor’s degree in Philosophy at SFU, where his minor in Social Data Analytics exposed him to data science and NLP. After pivoting away from Philosophy, Saumi started working on a data analyst portfolio to try to land a position as a data analyst. However, he realized he needed more schooling, which led him to apply to the MDS Computational Linguistics program.

Saumi added that the MDS Computational Linguistics program gave him access to a lot of technical knowledge and jargon that one would likely struggle to acquire doing their own research. “This field moves really fast, so having access to people who are knowledgeable enough to give you the fundamentals while also covering some recent trends is really hard to get anywhere else.”

Because Saumi’s background was in the humanities, he came into the program with little experience in R and Python, finding the transition to such a technical field both intimidating and exciting.

“I tried to focus on my curiosity and passion for learning to carry me through periods of self-doubt and confusion. People coming from non-CS backgrounds will struggle more than others, but my advice is to stay curious: ask stupid questions, and raise your hand in lecture to stay engaged. I cannot stress enough that learning is your goal here; your grades and accolades will follow,” he noted.

During the program, Saumi said his favorite course was DSCI 572 (Supervised Learning II), as it was his first foray into neural networks and one of the most challenging courses. “Neural networks are the family of models underpinning LLMs and AI, so really getting to the root of how these things are constructed and how they train was really important.”

He added that the second half of the MDS Computational Linguistics program does a good job of covering LLMs and AI, from fundamental concepts to modern trends.

In addition, Saumi really enjoyed meeting people in his cohort who came from diverse backgrounds.

“You end up learning a lot about other cultures and other academic disciplines. It also gives you a sense of the diversity of the industry you (in theory) would work in, which is really helpful if you’re coming from a non-technical background,” he elaborated.

Another aspect that prompted Saumi to apply to the MDS Computational Linguistics program was the capstone project. The capstone was Saumi’s opportunity to work with a real company, helping him become familiar with how things move in the industry.

“During the capstone project, I really pushed myself to take an active role in project leadership. In previous projects, I’ve been happy to help whenever I can and contribute to leadership only when someone else didn’t want to. I felt that I learned a lot about how to work with other people in a way that doesn’t become overbearing or monopolizing. I hope to continue improving my leadership skills in the future,” he added.

As he prepares to enter the workforce, Saumi said the program helped him enhance his communication skills, as well as his ability to work with others remotely, which he hopes to carry with him into his first job.

In terms of roles, Saumi is looking for data scientist, ML engineer, and AI engineer positions.

Saumi’s Top 3 Tips on Succeeding in the MDS Computational Linguistics Program:

1. Stay curious.
2. Make friends with your peers and profs.
3. Take care of yourself: exercise, eat and drink.

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