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Peter Tea is a Data Scientist at SMT, where they build descriptive and predictive dashboards using R and D3. Prior to this role, Peter has worked as a Quantitative Analyst Intern at Canada Revenue Agency, Data Science Intern at Aquatic Informatics Inc., Data Research Consultant at Simon Fraser University, Policy Analyst at Transport Canada, Undergraduate Research Student at University of Ottawa, and Undergraduate Research Assistant at University of Ottawa. Their experience includes deciphering patterns in tax-evasion behavior, applying anomaly detection algorithms, consulting on graduate research projects, monitoring trends and risks in transporting dangerous goods, investigating Machine Learning kernel methods, and compiling reports illustrating statistical methods applications.