Argho Das, Edric Svarte, and Matthew Badal-Badalian all joined the Master’s in Data Science and Artificial Intelligence (MDSDAI) program in 2023. We talked to them about why they chose the program, what they learned during their co-ops, and how their experience in the program has prepared them for their careers.
L-R: Argho Das, Edric Svarte, Matthew Badal-Badalian
Why did you choose the MDSAI program?
Argho Das: I still remember a lecture where the professor spoke passionately about the transformative impact of AI on industries like healthcare, finance, and beyond. My ultimate goal today is to contribute to AI healthcare solutions, resulting in faster and more accurate treatment for patients. The MDSAI program is a great stepping stone for my career transition from academic study to the AI industry.
Edric Svarte: I did my BMath at Waterloo as well, and discovered a passion for statistics and computer science that made the MDSAI program seem like an attractive field for my interests.
Matthew Badal-Badalian: I was particularly interested in the in-depth courses on deep learning, neural networks, and artificial intelligence. The structured approach to machine learning theory, combined with hands-on applications, aligned perfectly with my ambitions.
Where did you do your co-op? What were some of the challenges, triumphs, and learning experiences?
Argho Das: I did an 8 month co-op at the Canadian Intellectual Property Office (CIPO) in Gatineau, Quebec. One of the most memorable aspects was working on a machine learning project that integrated both text and image data to measure patent similarity – I had primarily worked with single data modalities before.
Beyond technical work, I loved collaborating with my team. The experience showed me that being a data scientist is as much about storytelling and collaboration as it is about crunching numbers.
Edric Svarte: I worked in the supply chain department of IPEX North America, a manufacturer and distributor of thermoplastic pipes and fittings. I think the biggest challenge was understanding the extremely complex business, and communicating with domain experts. These individuals help data scientists comprehend the data and results by providing critical context, but they use a lot of jargon and can take time to build relationship with. It felt really good to apply skills I had learned in graduate school to the workplace!
Matthew Badal-Badalian: I worked as an AI Intern at the Royal Bank of Canada, on the same team where I had previously interned as a Data Science Intern during undergrad. One of the most memorable aspects of my co-op was working with Large Language Models (LLMs) and advanced AI tools including ChatGPT-4 and CLIP. One of my most impactful projects involved designing a multimodal webpage classification system that combined a CLIP-based neural network with an ensemble learning model, achieving high accuracy in classifying web content.
How have your classroom and co-op experience prepared you for your career?
Argho Das: The MDSAI program has been instrumental in shaping my journey. The program gave me a strong foundation in machine learning, data science, and AI, which I’ve applied not only in academic projects but also during my co-op. My experience at CIPO allowed me to build on this knowledge by working on real-world challenges, like integrating text and image data for patent similarity detection. I learned how to apply advanced AI techniques in practical settings, manage large datasets, and communicate technical findings to diverse stakeholders.
Edric Svarte: I worked in the supply chain department of IPEX North America, a manufacturer and distributor of thermoplastic pipes and fittings. I think the biggest challenge was understanding the extremely complex business, and communicating with domain experts. These individuals help data scientists comprehend the data and results by providing critical context, but they use a lot of jargon and can take time to build relationship with. It felt really good to apply skills I had learned in graduate school to the workplace!
Matthew Badal-Badalian: My co-op was instrumental in helping me bridge the gap between academic theory and real-world applications. It helped me develop a structured, research-driven approach to problem-solving, and also strengthened my ability to communicate complex AI concepts to diverse audiences, which is crucial for industry collaboration.
Whether you want to go into health care, manufacturing, finance, or blaze your own trail, the MDSAI program will help you build the skills you need!