Data Science Industry Panel Networking Event
The Data Science Industry Panel Networking Event is an exclusive yearly event for all Data Science and Artificial Intelligence (MDSAI)/co-op and Master of Mathematics (MMath) in Data Science students. The event is a platform to connect accomplished industry experts from the Data Science Advisory Board with aspiring Master of Data Science and Artificial Intelligence (MDSAI) students. The event aims to provide students with valuable insights into the data science field through a panel discussion with industry experts, offering career advice, networking opportunities and the opportunity to cultivate valuable connections.
Fall 2025 Industry Panel Networking Event
We are pleased to announce our annual exclusive Industry Panel Networking Event featuring a distinguished panel of industry experts. Join us on Monday, November 24, from 3:00 PM to 6:00 PM for an afternoon of insightful discussions and networking opportunities.
Event Highlights:
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Distinguished Panel of Experts: Engage with industry leaders as they share their expertise on key topics such as current industry trends, breaking into data science and career growth!
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Interactive Panel Discussion: Pose your questions and gain valuable insights directly from our panelists, enhancing your understanding of the industry landscape.
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Networking Opportunities: Connect with panelists and fellow graduate data science students, fostering relationships that can support your career development and co-op opportunities.
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Complimentary Refreshments: Enjoy delicious refreshments while you network and engage in meaningful conversations
This is a unique opportunity to learn from and connect with leading experts in your field. We look forward to seeing you there!
Invitation only event. Please check your email on how to register!
Schedule
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Time |
Activity |
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3:00 pm |
Event Begins |
|
3:30 pm |
Welcome Remarks & Introductions |
|
3:35 pm |
Panel Discussion Begins |
|
4:35 pm |
Panel Discussion Ends & Closing Remarks |
|
4:45 pm |
Networking & Refreshments |
|
6:00 pm |
Event Ends |
Participating Industry Partners
Panelist Profiles
Alex Coman | Google Inc.
As Director of Engineering for Google Ads, Alex is responsible for the infrastructure systems that power the open and free internet across the ad-supported web and apps ecosystems. Alex’s focus is on evolving the ad serving infrastructure with the help of his teams, towards supporting Google’s ad business evolution, delivering high performance at internet scale, and ultimately helping Google Ads to create value for users, publishers, advertisers and Google. Prior to joining Google Ads, Alex has contributed to other Google products such as Google Search, Google’s foray into social networks and Google Shopping. Alex holds a Ph.D. in Computer Science from University of Alberta with specialization in Data Management.
Harper Forbes | Hoffmann-La Roche
Harper Forbes is the Director of Data Sciences at Hoffmann-La Roche with 25 years of experience in the biometric pharmaceutical research industry, specializing in Biostatistics and Statistical Programming. As a people and product leader, Harper guides global projects and develops teams of statisticians and programmers across multiple therapeutic areas. Expertise includes statistical methodologies and strategy for clinical development. Embracing innovation, Harper actively promotes the incorporation of AI to create efficiencies in coding, data interpretation, and communication. Throughout his career, Harper has consistently focused on recruiting, developing, and mentoring talent in the data science field. Harper has a Masters of Science in Statistics from the University of Guelph.
Bethany L. | Canadian Centre for Cyber Security
From a background of Math, Theoretical Linguistics, and Computational Linguistics, I worked in academia then applied Data Science within the Government of Canada. I draw on a deep understanding of language data combined with technical skills to create automated processes and Machine Learning enabled applications to support frontline analysts and wrangle real world data for productive use.
Miguel Lacerda | Balyasny Asset Management
Miguel Lacerda is the Director of AI Enablement at Balyasny Asset Management. Prior to this, he was the Chief Data Scientist at a boutique asset management firm and the Group Head of Advanced Analytics at a large financial services company in South Africa. Before moving into the private sector, he was a Lecturer and Researcher at the University of Cape Town, where he led the development of the first undergraduate and masters programs in Data Science in the country. He holds a PhD in Mathematics from the University of Galway in Ireland.
Eric Morrow | BMO Financial Group
Eric is currently the Managing Director of the Enterprise Data Science & AI group within BMO's Data and Analytics (DnA) organization. As a horizontal function within BMO, his team of data scientists and AI developers engages with groups and services across the organization to develop anything from data-driven insights to production ML/AI-based solutions on topics ranging from price optimization to cybersecurity-threat detection and beyond.
Prior to BMO, Eric worked in the aerospace industry on spacecraft development and robotic operations on the International Space Station. He has also worked in the exploration geophysics field on innovative gravity measurement systems.
Eric holds a PhD in geophysics from Harvard University and Masters degrees in physics and aerospace engineering from the University of Toronto.
Eric Rancourt | Statistics Canada
Eric Rancourt is Assistant Chief Statistician and Chief Data Officer at Statistics Canada where he has had multiple roles over the last 35 years. He is responsible for strategic data management, methodology and analysis. These include data standards, quality, registers, geographic systems, modelling, data science, AI, ethics, privacy, and legal aspects.
Eric is Chair of the Board of Governors of the Canadian Statistical Sciences Institute (CANSSI). He co-chairs the Assistant Deputy Ministers Committee on Data and Information and the Standards Council of Canada’s AI Data Governance Collaborative. He is also a member of the Canadian Research Data Centre Network, a member of the National Data Advisory Council of Australia and a member of the Abu Dhabi International Statistical Advisory Committee. Eric has been active in the fields of data representativity, administrative and alternative data, data frameworks and data ethics. His academic background includes degrees in statistics, history, and philosophy. He is Chair of the Survey Methods Section of the American Statistical Association; Chair of the Board, Survey Methodology Journal and is an elected member of the International Statistical Institute.

