Azar Taheri Tayebi

Detail-oriented Data Analyst with extensive experience in statistical machine learning, data visualization, and predictive modeling. Proven ability to utilize Python, R, SQL, and Tableau to convert complex datasets into actionable insights. Expertise in anomaly detection and various machine learning techniques drives effective solutions for business challenges and enhances decision-making processes.

• Machine Learning and Data Analysis Certificate, NexaLand School, 01/01/24
• Machine Learning with Python, Maktabkhooneh Institute, 01/01/21

• Teaching Math of Finance and Biostatistics, Niagara College and Brock University, 09/01/23, Present
• Published a paper on fishing catch rates and durations, arXiv, submitted to the Canadian Journal of Fisheries and Aquatic Sciences
• Awarded Best Poster at AI Day Conference for Modeling Fishery Variables, 01/01/23
• Secured the NFRF Grant for Rapid Response to Emerging Fisheries Issues in Canada, 01/01/22
• Co-authored the book Integral and Differential Calculus, 01/01/11

Positive-Unlabeled Fraud Detection, Simon Fraser University, Burnaby, BC, Canada, 01/01/24, Present, Designed and implemented autoencoders to detect fraudulent activities in the U.S. healthcare system., Evaluated model performance rigorously, refining methodologies to improve detection accuracy. Statistical Modeling of Fishery Variables, Brock University, St. Catharines, ON, Canada, 01/01/22, 12/31/24, Developed a Python-based pipeline for data collection and preprocessing., Built and validated Bayesian Network models in R to predict catch rates and fishing durations., Applied Bayesian Model Averaging to quantify uncertainty and improve model reliability.