Fin-ML
Catherine Paradis-Therrien is an accomplished professional with extensive experience in data analytics, insights, and AI, currently serving as the Associate Vice-President at TD since January 2007. Leading a diverse team of data experts, Catherine focuses on developing strategic analyses and predictive models to drive business decisions in Canadian banking. Previous roles include Senior Manager for analytics in customer-centric solutions and advanced analytics at TD Assurance, where Catherine enhanced client acquisition and retention through innovative modeling techniques. Additionally, Catherine has contributed as a consultant in statistics, a lecturer on statistical software, and an actuarial analyst, with a strong educational background in Statistics and Mathematics from Université de Montréal. Currently, Catherine serves as a mentor at Fin-ML.
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Fin-ML
The Fin-ML network aims to become a Canadian reference for acquiring specialized skills in the field of innovative machine learning technology in quantitative finance and financial business analytics. Our diversified team is composed of researchers, students and professionals with an internationally recognized scientific expertise covering a wide spectrum of fields at the crossroads of mathematics, computer science, artificial intelligence, business analytics and quantitative finance applications. We offer: - activities (workshops, conferences, seminars, etc..) geared towards finance students and professionals seeking to understand and implement innovative machine learning techniques. - our NSERC-CREATE Program in Machine Learning in Quantitative Finance and Business Analytics is offered through a competition to students in participating universities across Canada. - to conduct and implement innovative and multidisciplinary collaborative research projects, small or large in scale, in order to offer our researchers multiple opportunities for industrial experience, locally or internationally. Fin-ML seeks to form a new generation of finance professionals to meet the modeling and implementation needs of the quantitative spectrum of the Canadian financial industry and contribute to its global competitiveness.