Since the 5G technology has already been well-developed, the information transmission rate will increase sharply, allowing more data to be collected by Internet companies. These companies, who are also service providers, will need more data analysts and business analyzers to help process data and provide customers with various new services to meet customers’ de[University Name]d. For example, I would recommend Spotify users with songs they may like basing on what genre of music they listen often, and recommend videos, movies or dramas to YouTube and Netflix users basing on their searching or watching history. By analyzing users’ shopping habit or de[University Name]d and recommending them with proper products, I could increase customer loyalty so that both users and companies can benefit from it.

Except for user analysis, data analysts also help improve decision-making and business models by digesting huge data. For example, the operating model of Spotify, quite similar to buffet restaurants, as people pay the same amount of money and they can listen to music as much as they can, needs for improvement. This model cannot bring profits because it does not make full use of data collected from users. If Spotify can analyze different users and make ‘smart contract’ for different users, give discounts to users who do not use the application quite often and provide more considerate services to users listening all day, it is likely to reverse the deficits. As a perfor[University Name]ce improvement specialist, I would help the company transform their traditional approach to decision making through data, information and intelligence.

Moreover, data science is applicable in [University Name]y other areas, such as food delivery, logistic industry and navigation service. For example, I can predict how long it will take for the restaurant to prepare the meal according to order quantity and estimate delivery time basing on road conditions. Companies, like Amey Strategic Consulting, need strategic consultant to engage with new technology, develop skills within the team, and build new tools and packages. Inspired by the future it would lead to, I am very determined to be a data scientist and I believe studying MSc Data Science at the [University Name] is of great help to achieve this goal, because courses in areas of Machine Learning, Statistics and Analysis will help me achieve my career goals.

Being a data scientist requires computational and analytic skills, logic thinking and cooperating with others. Firstly, I chose Java in Year-1 study, and I learned basic knowledge of programming. Along with the preliminary understanding of Python learned via Coursera, I believe that the course Programming in Python for Business Analytics will teach me to use Python packages for not only data analysis and visualization, but also optimization and decision support. Moreover, other courses I took can help me with postgraduate study. I took two Calculus courses, i.e., Multivariable Calculus, Introduction to the Methods of Mathematics, two courses of Linear Algebra, i.e., Linear Algebra for Mathematics, Linear Algebra and Geometry, three courses in Statistics, i.e., Introduction to Probability and Statistics, Statistical Theories and Methods II, Linear Statistical Models, four courses in Probability, i.e., Introduction to Probability and Statistics, Statistical Theories and Methods I, Applied Probability, Operational Research: Probabilistic Models. With such solid foundation, I will adapt quickly to the master’s programme and contribute to the cohort.

Secondly, during my undergraduate study, I took 2 courses of Analysis. Since this course focused on Mathematical theories, I learned to not only apply mathematical model into analysis, but also make arguments basing on facts and concrete information. Also, I am interested in how things work, and tend to break things down when it is difficult to understand. My interest in theoretical models and explanations encourage me to dive in the postgraduate study. I have also been a member of a research project. In this research, we collected data from both the Internet and real-world surveys to figure out how windows of different brands were designed and customers’ brand perception. Using STATA to analyze data with the linear regression model, we found that People's affection for the brand is directly proportional to the cleanliness of the window and they aspire to see clearly what the brand wants to show when they pass the window, while whether the window is gorgeous or not has no obvious relationship with consumers' cognition of the brand.

Finally, business analyzers need to be flexible to fit in a team. I once participated in a remote internship program for Kraft-Heinz, a project requiring us to use business analytics skills to analyze college students about how much they know about FMCG companies and their willingness to work in an FMCG company after graduation. This project lasted for 6 weeks and I was the leader in week 2. My task was to lead the team to design the questionnaire distributed to college students. As a leader, I preferred making the group focus on those most important things and allowing members to work with their own ideas with only a general direction decided. We finally decided several possible factors, such as their major, the location of their college, and their career plan, especially the expected salary and their expected work environment, to be used to check which factor might affect college students’ knowledge about FMCG companies and whether they aspire to enter an FMCG company. I believe my willingness to cooperate and my skills in leading and working with a team will help me adapt quickly to the environment and help others contribute more.

The [University Name] enjoys a reputation for ground-breaking research and innovation. I believe I have readied myself to enjoy the spirit and environment to breed such research and innovation and make my own contribution to maintaining this great reputation and pushing it to a higher level.