Thomas Van Zuiden

Thomas Van Zuiden

Sr. Data Scientist, Advanced Analytics Delivery @ Interac

About Thomas Van Zuiden

Thomas Van Zuiden is a Sr. Data Scientist specializing in advanced analytics and predictive modeling at Interac Corp. He has a strong background in natural language processing and has held various roles in data science and analytics across several organizations.

Work at Interac

Currently, Thomas Van Zuiden serves as a Senior Data Scientist in Advanced Analytics Delivery at Interac Corp. since 2020. In this role, he has developed advanced predictive modeling solutions and contributed to the field of natural language processing as a subject matter expert. His work focuses on leveraging data to provide insights that enhance decision-making processes within the organization.

Previous Experience in Data Science

Prior to his current position, Thomas worked at Interac Corp. as a Specialist in Advanced Analytics & Data Science from 2019 to 2020. He also held the position of Modelling/Forecasting Analyst - Advanced Analytics at TD Insurance from 2017 to 2019. His earlier experience includes roles as a Data Manager and Statistical Analyst at York University from 2015 to 2017, and as a Research Student at The Hospital for Sick Children in 2010.

Education and Expertise

Thomas Van Zuiden holds a Master’s Degree in Biology with a focus on quantitative ecology from York University, where he studied from 2013 to 2015. He also earned a Bachelor’s Degree in Biological Sciences from Queen's University, completing his studies from 2006 to 2010. His academic background supports his specialization in Python programming for data-driven insights.

Teaching Experience

During his academic career, Thomas served as a Teaching Assistant at York University from 2013 to 2015. In this role, he contributed to the education of students, providing support in various subjects related to data science and biology. His teaching experience complements his analytical skills and enhances his ability to communicate complex ideas effectively.

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