Bringing Data Science Forward

Milind Thummala (MSAI '23) remembers being a teenager watching videos on YouTube and movies on Netflix and being struck not by what he was watching, but by what the platforms thought he should be watching. 

Seeing what each platform recommended he watch based on his viewing history is the first time he remembers interacting with AI. It wasn't long after that he began exploring AI and considering how he could build a career leveraging the technology. 

"I thought it to be very cool to recommend to users what they might be interested in among millions of videos," Milind said. "I was intrigued at how AI could be used for automating and decision making with logical workflows." 

Milind now uses AI for automation and decision making on a daily basis as a data scientist at TerraStrat, a startup focused on data science for financial institutions and healthcare organizations.  

Milind works with banks and credit unions to analyze branch location analytics, perform customer and prospect segmentation, and build predictive marketing models. He also supports healthcare companies by modeling supply-and-demand scenarios across the US.  

"It is very interesting to see models you build being actively used by clients for strategizing," Milind said. "It is very challenging to work on modeling and scoring locations because of the difficulty of the problem, but that's what excites me." 

Milind joined TerraStrat in January 2024. Initially his focus was on simple automation tasks, but his responsibilities quickly evolved to include more complex opportunities and workflows. That rapid evolution is one of the benefits of working at a startup, he said. 

He also credited his experience in Northwestern Engineering's Master of Science in Artificial Intelligence (MSAI) program with preparing him to thrive in his current role. 

Milind was drawn to MSAI because of the structure of the program and its emphasis on project-based work. 

"The program’s curriculum was well-structured and easy to follow, yet it covered a wide range of AI topics in depth," he said. "It even included courses like Human-Computer Interaction and a capstone project, helping students prepare for careers in the AI industry rather than focusing solely on research." 

Milind routinely applies lessons learned in the classroom to his daily work. His Intro to Databases course prepared him with concepts and best practices for working with large data — lessons that are beneficial when working with datasets filled with nearly one trillion rows of information.   

"The concepts I learned in that course were super useful as they apply to all AI systems," he said. "With a lot of my current company’s clients being financial institutions and having to work with large amounts of data, foundational concepts to work with and manipulating large data for AI systems are learnings I find super useful."  

He appreciated the program's focus on current industry trends like natural language processing. He also benefited from his capstone experience and the opportunity to collaborate with classmates to solve a real company's business problem.  

Now he's taking those lessons and regularly incorporating them as he looks to solve other companies' business problems. 

"MSAI gave me a lot of perspective on working on real world projects, which allowed me to quickly gain skills that are useful in industries I did not have prior work experience with," Milind said. "The program allowed me to gain well-rounded growth in foundational topics currently being used to build AI systems."