Tim To
About Tim To
Tim To is a Senior Manager at CIBC specializing in AML Analytics with a background in data science and fraud analytics.
Current Role at CIBC
Tim To currently holds the position of Senior Manager, AML Analytics at CIBC in Toronto, Ontario, Canada. He has been with the company since 2019. In this role, he oversees anti-money laundering (AML) analytics, contributing to the development and implementation of models and strategies to detect and prevent fraudulent activities within the financial institution.
Previous Experience at TD Bank
Before joining CIBC, Tim To worked at TD Bank in Toronto, Canada Area where he held two distinct positions. From 2017 to 2019, Tim served as a Data Scientist in AML Analytics, focusing on data analysis to mitigate risks related to money laundering. Prior to this, from 2014 to 2017, he worked as an Analyst in Fraud Analytics, tackling issues related to fraudulent activities through data-driven approaches.
Role at Sanofi Pasteur
Tim To worked at Sanofi Pasteur as an Associate Scientist in the Vaccine Development team from 2012 to 2013 in Toronto, Ontario, Canada. During this period, he was involved in the research and development of vaccine candidates, contributing to scientific studies aimed at enhancing vaccine efficacy and safety.
Position at Roche
Tim To spent three years at Roche from 2009 to 2012, first in Toronto, ON, Canada and later in Nutley, NJ, USA, as a Senior Research Associate in Cancer Drug Discovery. In this capacity, he was engaged in cutting-edge cancer research, focusing on discovering and developing potential therapeutic drugs aimed at treating various forms of cancer.
Educational Background
Tim To has an extensive educational background. He earned two Master of Science (MSc) degrees from the University of Toronto, one in Biostatistics and another in Molecular Genetics. He also holds a Bachelor of Science (BSc) in Molecular Biology & Biochemistry from Simon Fraser University.
Technical Skills and Projects
Tim To has developed custom interactive visualizations using D3.js to improve data presentation. He utilized web scraping techniques to gather information from various sources and construct new databases. He implemented machine learning models using Python libraries such as sci-kit learn, Keras, and TensorFlow. Additionally, he has experience in creating web applications using React.js with Flask or Django backends for data visualization purposes.