Motivated by my passion in math and finance and aware of the significance of the role technology plays in the financial world today, I devoted myself to discovering the field of Financial Engineering throughout college. My comprehension of the fundamental, quantitative, and technological aspects of finance has been cultivated and strengthened as result of my academic and professional experiences. These experiences initiated my interest and consolidated my potential to pursue a career in quantitative finance with projects in implementing math models with advanced machine learning for financial risk assessment and Algorithmic Trading. Graduated with a Mathematics Bachelor degree and an Applied Mathematics Minor from the University of Washington (UW), I have taken many Mathematics and Computer Science classes. They granted me the solid financial mathematical knowledge and programming skills in Java, C++, R, MATLAB, SQL and VBA. Nevertheless, I took initiative and successfully completed four graduate level classes offered by the UW Computational Finance and Risk Management Program, and was qualified to receive the Quantitative Fundamentals of Computational Finance Certificate. I was mostly inspired by the class “Trading System”, which exposed me to the Algorithmic Trading area. This class instructed me how to research, design, implement, test and deploy automated quantitative trading strategies in R and practice them with the Interactive Brokers Trader WorkStation’s simulated trading platform. I was impressed by the verifiability, quantification, consistency, and objectivity of technology regarding trading, and they inspired me to make further exploration to the Algorithmic Trading area. Driven by my inquisitiveness in Finance, I got involved in a venture capital research project at the UW Michael G. Foster School of Business, applying my quantitative skills to study the risk choice of investment as firms face financial distress. During this process, I embraced a deeper understanding of finance and research, and simultaneously discovered that I was both an innately inquisitive person who was interested in miscellaneous knowledge and a deliberate person who possesses the ability to broaden and deepen my knowledge. I was motivated to further investigate those potentials combined with fundamental and quantitative analysis through applied research, as the success in the quantitative finance field based on merit, dedication, and knowledge. In addition, a competitive Quant should also be an excellent communicator as he or she may be required to present his or her findings to clients. During junior year of college, I intentionally practiced my communication and many other social skills. Inspired by my deep passion for quantitative finance, I co-founded the UW Financial Engineering Club, which provided a platform for undergraduate students who were as interested as me in Financial Engineering to network with industry professionals, as well as to be in touch with the forefront financial industry trend. This experience cultivated my qualities of effective communication, problem-solving, leadership and teamwork skills. I will continue to learn how to apply those qualities to my advantage in my future career of quantitative finance. From the previous club experience, I was aware that, in the area of finance, working experience provides an advantage over academic study, as it can offer technical training and exposure to the financial market. My current internship at Siemens Financial Service Ltd. (SFSL) provides me with a substantial experience in the intersection of finance and technology. I am deeply involved in five financial projects, in which my duties include but are not limited to data analytics and VBA programming for transaction system construction. It applied my quantitative knowledge in practice and improved my data analytic ability. Besides, the Global Market department functioned as the front office, whose busy environment also trained me to work under pressure and alone with people. Therefore, this internship reinforced my dedication to pursue the career path of quantitative finance in a leading investment bank. Throughout my past four years of experience in college and industry, I have gained a broad understanding and the necessary skill sets for a career in quantitative finance. Possessing both quantitative research and data analytic skills, and interest in trading, I determined to pursue the career path of quantitative finance, and to be specific, in the field of Algorithmic Trading, developing optimal trading strategies and profitably promote rapid trade in a leading investment bank. I envision the Master of Financial Engineering program at UCLA as an ideal platform to achieve this career goal. Its rigorous curriculum designed around the most cutting-edge financial and quantitative theories and practices, and renowned faculty and business school resources supported by the dedicated professional development assistance, will offer me a unique advantage when hunting for placement in the United States. I am confident that I can build up my quantitative competence and my well-rounded experience in the UCLA Master of Financial Engineering program to excel in the quantitative finance career path.