润色如下内容：I started to attend series of seminars and workshops on big data analysis and was impressed by innovative applications of big data in business analytics. However, during my internships in financial institutions in China, I realised that the inefficient utilisation of data has discouraged business growth and performance, such as lacking feasibility by only analysing YoY or MoM data. By undertaking multiple data-related modules, I obtained in-depth perceptions of data as a major drive of business development and policy improvement. Further inspired by advanced technologies such as AI-driven operation during my internship at Tencent, I became aware of the significance of technological innovation in business development for firms and the necessity of obtaining leading knowledge of statistics, computer science, and business analysis to support my future career. The ChatGPT, intelligent manufacturing, and many other epoch-making techniques have been accelerating the great diversion of industrial structures and rapid growth in many industries, while the application of these techniques also requires revolutions of business and management skills. As such, it becomes extremely important to receive cutting-edge theories of business research and have access to high-end technologies that can fuel corporate growth, which encourages me to apply for the Master of Science in Business Analytics at the University of Hong Kong. I believe that my academic and professional experiences have equipped me with essential qualifications and hope to cultivate my statistical and analytical skills if I could have the opportunity to join you.

Academically, I completed major modules related to business and management, such as Accounting Analytics for Professional Accountants, Time Series Analysis and Forecasting, Business Modelling and Optimization, and Data Mining for Business Analytics during my bachelor’s studies. For instance, the module Time Series Analysis and Forecasting focuses on how to deal with big data from the perspectives of time series. I applied time-series theories taught in this module to my internship at Tencent by assigning higher weighting coefficients to recent years and lower coefficients to distant years to provide a more feasible estimation of the data of digital game players in different countries. Besides, I have undertaken statistics and computer science modules such as Introduction to Computer Science and learned the basics of programming, IU design, and computer graphics from this module, preparing for my proposed future research on business analysis based on programming languages. By participating in multiple research projects, my research skills were significantly improved. In a project of estimating economic, financial, and business time-series patterns based on R, I joined in the research group and completed the estimation using theories of moving averages, exponential smoothing, Box-Jenkins, and ARIMA models. In another project of assisting a Portuguese retail bank to determine the effectiveness of their direct marketing campaigns to sell a long-term deposit using data mining theories, I constructed correlation matrix screening indicators for numerical attributes and normalization and performed discretization on classification attributes by removing time-related indicators irrelevant to the willingness to purchase products. Then, I established three main models, i.e., Decision Tree, Logistic Regression, and Naive Bayes models to analyse the effectiveness of marketing campaigns. The final result of this project demonstrates a 20% increase in the accuracy of modelling estimation after rounds of calibration and robustness tests. This experience granted me a profound comprehension of data analytics and its significance in business analysis. It also enlightened me to the fact that establishing a predictive model requires a deep understanding of relevant business and the ability to convert decision-making ideas in actual work into modelling thresholds.

Professionally, benefiting from several internships, I have had close contact with advanced business and management practices in world-leading companies. When I worked as a Global User Geographic Distribution Research Assistant at Tencent, I conducted preliminary background checks for the production of overseas games produced by Tencent and assisted the user research department in summarising some heterogeneous characteristics of game players and gaming behaviours in various countries. First, it is essential to compare the results of Newzoo and Tencent's internal survey of game players in multiple countries and evaluate whether Newzoo data can cross-validate Tencent data. Second, it was finished with desk research, i.e., explaining the differences between gamer behaviour and expectations in the four countries, namely Turkey, Mexico, Brazil, and Malaysia from the aspects of culture, economy, and policy. I also faced challenges during the process of completing this task, such as missing different behaviours of answering survey questions among game players from different countries. I realized that when the results of the questionnaire are presented, I should first think about the idea of designing the question and who is the group of interviewees that responded, and then analyse the results of the questionnaire. Additionally, when I conducted desk research into the reasons for differences in gaming behaviour and expectations between countries, I initially only looked at current data and ignored the fact that it takes time to develop collective habits and current behaviour can often be traced back to the level of economic development, equipment accessibility, and traffic availability in the past five or even ten years. 

I also have experience in establishing an automated rating system by collecting data on ABS products, analysing theoretical concepts of ABS, and consulting with experts on solving data problems during my internship at the PwC consulting firm. As an Internet industry research intern previously at Oriental Security, I was responsible for the daily research, collection, and organization of data related to major online shopping and e-commerce platforms in China, focusing on community e-commerce and other subdivisions, gaining insight into changes in consumer trends, and organizing quarterly reports of listed companies such as Tencent, Meituan, and NetEase, and completed Analysis of Meituan’s 2Q21 and 1Q22 business performance to evaluate the company’s potential value growth points and business model feasibility. It is important to note that there is a large amount of data in industry research and consulting work, while obtaining data is still highly dependent on labour. Given that the programming automation process can be utilised, the efficiency of data analysis in major financial institutions can be extremely improved. In addition, analysts only use the most basic methods based on descriptive analysis of charts and draw conclusions based more on intuition rather than rigorous argumentation methods, which might lead to modelling bias and negative impacts on the decision-making process. As such, I hope to gain advanced theories and practices of data analysis to support a more sustainable and reliable operational system. 

The University of Hong Kong is a leading university that owns a reputation for its academic excellence especially in the field of business and management and is much closer to the city centre of Hong Kong, which provides the convenience of internship and commuting. The Master of Science in Business Analytics programme combines advanced business theories with adequate opportunities for internship in major corporations. Additionally, the well-designed structure of curriculum can equip me with skills of data acquisition and analysis by undertaking modules of Database Design and Management, Prescriptive Analytics, and Machine Learning, and fulfil my hope to learn consumer research methods by learning marketing analytics, social media, and digital marketing analytics. The project of capstone can further fuel my employability due to its growing importance in numerous firms. My short-term career goal is to work as a data analyst focusing on data mining, data analysis, or data operations in an Internet company or consumer-industry company and become a professional product manager in 3-5 years by establishing models and improving the business modes to support the company. I also noticed that the Hong Kong government is currently promoting the development of AI, big data, and Internet-related innovations to boost the sustainable development in Hong Kong, which is a great opportunity for me to contribute to this process and the digitalisation of business behaviours. My long-term career objective is to venture into the entrepreneurship and start up my own business by designing a product that make daily lives more convenient and delightful.