Transitioning from Intern to Associate

What are the most effective ways to promote a protein manufacturer?  

That was a question Ashwin Sundaramurthy (MLDS '25) never thought he would consider when he moved to Chicago from India to join Northwestern Engineering's Master of Science in Machine Learning and Data Science (MLDS) program. But thanks to his experience in MLDS, it was one he was prepared to answer. 

The challenge came from a meat production company during Ashwin's internship at Teragonia, a Chicago-based AI company focused on driving growth for private equity-backed mid-market companies. The client was running multiple promotions to boost its business and wanted to know what specifically makes one promotion effective and another fall short. 

“I used some of what I’d already learned in MLDS to determine a set of characteristics that make a promotion effective,” he said. “Then, I gave them an idea of how many promotions in the past have been effective.”  

The internship was a valuable learning experience for Ashwin, as well as for Teragonia. The company was impressed with his work and offered him a full-time position as an associate data scientist for after he graduates.  

Ashwin knew little about the company when he started in MLDS, but a Teragonia case study he found online got him intrigued. He learned more about the company and decided he wanted to intern there — but he didn't want to wait until the summer when the rest of the MLDS students complete their internships. 

He spoke with program administrators and began interning with the company on a part-time basis in February. Then over the summer, the internship became a full-time commitment.  

Having that hands-on experience at a company was a differentiator for Ashwin and one of the primary reasons the MLDS program appealed to him.  

“The MLDS program is really good with support in each and every part of the internship and job search processes,” he said. “When I read about a lot of other programs, they didn't have anything like it.”  

Ashwin had nearly four years of experience in data analytics and machine learning when he began in MLDS. He saw the program as an opportunity to accelerate his learning and career trajectory.  

As he began his Teragonia internship, he realized that was exactly what happened. Beyond helping with client work, the lessons Ashwin learned in MLDS became particularly helpful during a company-wide hackathon, where participants were tasked with creating a retrieval-augmented generation (RAG) system built with large language models (LLMs). 

Ashwin and his team won the competition.    

“The courses I’d already taken came in handy,” he said. “There were two, one on data mining and one that was specifically focused on generative AI that talked about large language models and these RAG systems that were helpful.”  

With his internship behind him, Ashwin is focused on completing his MLDS coursework and looking ahead to what he needs to achieve greater success when he returns to Teragonia.  

His capstone has him partnered with an investment firm, working on a project to understand the factors behind its fund churn. He's confident he will learn from that experience and is actively pursuing ways to practice his communication skills.  

His goal is simple: Take away as many lessons from MLDS as possible and apply them to his full-time role. One lesson he's focused on is learning to better explain his work to people without a data science background.  

"I'm continuing to learn," Ashwin said. "I'm trying to understand as much as possible before I get back into the real world."