Mathieu Lavallée
About Mathieu Lavallée
Mathieu Lavallée is a Senior Engineering Manager at CIBC specializing in machine learning, technical product management, and data science. He has a diverse background in software development, business strategy, and entrepreneurship, with a strong educational foundation in finance and computer software engineering.
Company
Mathieu Lavallée currently works at CIBC as a Senior Engineering Manager specializing in Machine Learning, Technical Product Management, and Data Science. He has been with CIBC since 2016 and operates out of the Toronto, Canada Area.
Title
Mathieu Lavallée holds the position of Senior Engineering Manager at CIBC, where his work focuses on areas such as Machine Learning, Technical Product Management, and Data Science.
Education and Expertise
Mathieu Lavallée has a strong educational background with a Master's degree in Business Administration (M.B.A.) from McGill University's Desautels Faculty of Management, which he earned from 2014 to 2016. Additionally, he holds a Bachelor's degree in Computer Software Engineering from Polytechnique Montréal, completed between 2007 and 2011. His formal education has given him a profound understanding of finance and engineering principles.
Background
Before joining CIBC, Mathieu Lavallée accumulated diverse experience across various roles and industries. He co-founded ClassKeeper, focusing on entrepreneurship, business strategy, sales, and full-stack mobile app development, from 2015 to 2016 in Montreal. Prior to that, he worked at Datahex Systems Inc. as a Software Developer Team Lead from 2011 to 2014, emphasizing Agile Scrum Master techniques and full-stack web app development. He also gained experience at IBM as a Product Manager Intern in 2015, participating in the Extreme Blue Leadership Program. Earlier in his career, he interned at CAE in Montreal in 2009.
Achievements
Mathieu Lavallée has several notable accomplishments. He won the Q4 2021 CIBC Momentum Award for leading the development of an innovative workforce optimization system. He designed a data architecture supporting machine learning models forecasting over 30 million data points weekly, saving millions in licensing fees with an in-house solution. During COVID, he developed a main absenteeism data source, delivered insights for senior executives, and made significant recommendations on data integrity and automation. Additionally, he played a key role in transitioning the Workforce team to advanced analytic tools like Tableau and Alteryx.