The reason why I aspire to pursue a master’s degree in Data Science comes from my work experience in Ernst & Young Huaming LLP as an auditor. I was a team member in the project of the initial public offering of Fosun Tourism Group (the Group), a wholly owned subsidiary of Fosun International Ltd., in Hong Kong. I was assigned to predict and analyze the price trend for the next three months in Atlantis Sanya, the comprehensive seven-star hotel in the Group. Because of a large amount of price information from hotels of the same type nearby, I spent three hours collecting it from websites. Then I organized nearly one thousand items of data according to hotel names and time periods, visualized the movement by using charts in Excel, and compared with that of Atlantis Sanya. Finally, I finished the analysis considering several factors, such as seasons, festivals, horizontal competition, etc. A few months later, I mentioned the experience with my brother, a computer engineer. He told me that I could’ve dealt with such data analysis using python with more efficiency. He showed me the same process with very little time.

Therefore, later I attended a project led by Ken Gleason, who was an adjunct Associate Professor in the Department of Industrial Engineering and Operations Research at Columbia University. In this project, I learned techniques closely related to financial engineering and multiple data structures as well as algorithms and mastered python skills to analyze stock prices in US Market. After many discussions and modifications, for the final presentation, my group designed a user-oriented program by defining different functions in python. We imported pandas and created DataFrame to manipulate tables of data. With the function of “add()”, users can put stocks with specific shares in their portfolios. Then they could get the information, such as historical and real-time stock prices, volumes and market value, cumulative return, variance, covariance, Sharpe ratio and Monte Carlo simulation about portfolios by entering different functions. By importing matplotlib, visualization diagrams were provided for better understanding. User can get the k line chart and macd lines of each stock by entering the function of “k_line(symbol)”. Besides, we defined functions to show correlation heatmap. With our program, even ordinary investors can get the data within several minutes to seize fleeting investment opportunities.

These experiences triggered my thinking of whether we could leverage technology to optimize auditors’ time, enable them to use their human judgment to analyze a broader and deeper set of data and documents. I found that some audit firms have already been exploring the potential power of machine learning in audits, such as Deloitte’s Argus for document interrogation and analysis. Later I read an article McDonald’s to Use AI to Tempt You into Extra Purchases at the Drive-thru on DigitalTrends.com, which introduced that McDonald was using smart technology to recommend products based on season, weather, and new or repeat customer preference. I realized that auditors could be able to use machine learning tools to gain a better understanding of the activity behind the numbers. By using supervised learning techniques, auditors could make independent predictions for analytical procedures. Unsupervised learning techniques could help reveal previously hidden risks. All of these make me deeply feel the changes the technology brought and inspire my interests to learn more knowledge and explore the potential of technology in the field of auditing or finance. So I would like to apply for the MSc in Data Science program at the [University Name] of Hong Kong.

The Program attracts me for the following reasons. Firstly, I love your rigorous curriculum. Statistical Machine Learning, which includes the knowledge of regression, classification, clustering, ensemble methods and other valuable contents, is practical,. The course of Exploratory Data Analysis and Visualization is taught with a series of case studies and hands-on projects, which is helpful for me to develop visualization tools for auditing in the future. Secondly, your joint laboratory with JD Digits attracts me a lot. I hope I will have an opportunity to explore new models and application of financial technologies in real-life projects.

Upon graduation, In the short term, I aspire to be a data analyst in audit innovation department in Ernst & Young. Within three years, by making full use of my previous audit experience and knowledge, I aspire to participate in the research and development of at least three new analytical audit tools or help optimize three existing tools, by which auditors could identify risks, investigate anomalies and visualize the analytical results more efficiently. I hope auditors could save half of their time by using such tools. At the same time, I will constantly update my knowledge and techniques related to this field. In the long run, I aspire to help businesses to become smarter, more productive, and better at making predictions. I aspire to lead a team and develop innovative products related to financial technology to help innovate the business decision-making process.

I look forward to embarking on a new academic journey with you and your colleagues in Hong Kong next year.