The Applied Statistics Program at XXXX University is my first choice since XXXX is close to where I live and I would have the full support of my social network and support base. Thus, I would be able to take advantage of the fullest immersion experience possible, giving myself fully to Statistics 24/7/
Born and raised in China, numbers have stood at the center of my world since my childhood because Mathematics was always what I did best and still do. Since early adulthood, I have increasingly gravitated towards Applied Mathematics as a focus, especially everything having to do with Statistics. I could not be happier fully engaged in the magic world of using numbers and symbols to solve real world problems.
After I graduated from high school, my family moved to Canada, and I was able to complete my undergraduate studies in Statistics, Actuarial Science, and Mathematics at the University of XXXX. Thus, I have had the opportunity to build a solid foundation in Statistics, including Advanced Calculus, Ordinary Differential Equation, Probability, Data Analysis, Multivariate Analysis, Time Series, and Stochastic Methods, etc. I graduated from UT with honors and went on to work in the banking industry.
In my third year at UX, I completed an internship in the development of Marketing models at the Analytics Resourcing Center, and I dove in head into the fascinating world of Big Data. I conducted customer segmentation analysis with extremely large volumes and high dimension data, campaign analysis, and promotion design for retail chain stores using Machine Learning techniques. This experience opened up my horizons greatly with respect to advanced modeling techniques and also helped me understand how to abstract statistical models in accordance with business needs. After graduation, I worked as an Actuarial Analyst for the School Boards’ Co-operative Inc.
I mastered the Mixed Effect model while working on a one-year statistical collaboration project on reduction in neuron cell experiments during my last year at UX. I now appreciate how the Mixed Effect has enormous advantage over the General Linear Model. Furthermore, by applying a Gradient Decent approach, I was able to optimize the model for my purposes and I was delighted with the results and was left feely most inspired about possibilities for applications. I soon began to realize that I have a gift for statistical modeling in detail and nothing brings me greater joy. This is where my passion lies.
Currently, I work as a retail risk model developer in TD bank, using classical statistical models. Since this position requires documentation of how each statistical decision is made, I have a chance to investigate numerous details about each algorithm. The most exciting part of Statistics for me is the challenge of finding ways to harness the power of scientific data to accurately predict real-world phenomenon. I see Statistics as a science capable of overcoming all kinds of challenges in the quest to maximize the utility of information. I have experienced how advanced statistical techniques can resolve data challenges in industry.
I look forward to a long professional lifetime serving as a researcher in the statistical modeling industry, discovering and resolving statistical challenges. For my purposes, Statistics is a scientific tool which harnesses the power of numbers for solving real-world problems. My diverse work experience with multiple industries has enabled me to gain exposure to a broad variety of modeling methods including but not limited to the classical linear model, machine learning and stochastic process. I have wrestled with many different kinds of data challenges from hundreds of observations that do not fit any frequently used distribution to billions of observations in thousands of dimensions. I thrive on the challenge of finding scientific ways to making less intuitive data reflect and accurately predict real-world phenomena.
I have used multiple machine learning techniques in Python and R platforms; and observed the pros and cons of cases while comparing different modeling methods. I understand and appreciate how retail risk models are long-term, predictive power driven. Accuracy, explanatory power and conservatism are equally important. I fully understand how, within the range of linear models, scientific support for each decision is needed; coefficient analysis between triple or quadruple interactions must be conducted; and how the survival and loss model is often of great utility. Always inspired by and engaged with the latest research topics, reading myself to sleep almost every night, even under a full workload with constant pressure. I especially enjoy the quest to prove the usefulness of a methodology via statistical and mathematical methods.
Committed, enthusiastic, and dedicated to what I love, I was given to music in my early years, since I was trained to become a professional classical pianist and came close to that dream. Now, however, while I still play sometimes to destress, my music is entirely in my head, symbols, numbers, real-world dreams in big data. Most of what I play these days is Jazz, in which I am self-educated. This inspired me to begin a non-profit music media company when I was in my 2nd year of college. I am also an accomplish programmer in R, Python and SAS. I also think of programming as part of the music that I want to make in the future.
I thank you for your consideration of my application to Applied Statistics at XXXX University.