Ming Yan

Background

About Ming Yan

As a data analyst and quantitative researcher with extensive experience in financial data analysis, statistical modelling, and data visualization, I excel in leveraging advanced tools such as Python, SQL, Excel, MATLAB, Tableau, and Power BI to drive operational efficiency and deliver data-driven insights. At the University of Toronto’s BRIDGE and African Impact Initiatives Project, I played a key role as a Data Engineer. My responsibilities included using Python to clean and preprocess large datasets, identifying and correcting data discrepancies,and significantly improving the accuracy of financial databases. In addition, I collaborated with a team to maintain these databases, ensuring their security and effective risk management. As a Financial Data Analyst at CICC in Shanghai, I automated the calculation of key financial metrics like current returns, maximum drawdown, and Sharpe ratio for Fund of Funds (FOF) products using Python, Xlwings, Pandas, and NumPy. This automation reduced report processing time by 30%. I regularly produced reports for institutional clients. Additionally, my data analysis on brokerage firms’ stock picks revealed predictive patterns that significantly impacted industry performance. These reports and insights were highly regarded by management and colleagues alike. As the teaching assistant at the University of Toronto, I demonstrated my ability to handle large datasets accurately. I managed the grading of quizzes and exams for a class of over 200 students, ensuring error-free results. My efforts led to a nomination for the UTSC Teaching Assistant Award, underscoring my commitment to academic excellence and leadership. As the Sponsorship Department Director for the Student Association at the University of Toronto, I increasing annual contracts from to