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스탠포드 대학원 지원 SOP(Data Science)에 대해 기술한 참고자료입니다.

저작시기 : 2021년 1월

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During my time as a procuremen
t associate in eTEC E&C, a South Korean EPC company that constructs civil buildings and industrial facilities, Ianalyzed data to attain information that greatly enhanced the efficiency of my work. For example, by scrutinizing information gathered from completed construction projects and their purchased equipment and materials, I found significant recurring patterns in terms of technical requirements and cost ratios. These patterns remained quite consistent when I applied them to ongoing and subsequent projects, making them invaluable references for planning budgets and estimating costs in the early stage of new projects.
However, I was facing analyti
cal challenges. To list a few, I was almost completely dependent on the company's internal data, and it was very difficult to decide where and how to find relevant, accurate data from credible sources outside the company. Next, analyzing data and information that continuously changed or was affected by too many factors, such as the performance and output of machineries, was problematic because such information was hard to standardize. Moreover, I needed a way to gather the necessary data automatically because mining data manually is time consuming and inefficient. I was thus curious about the way my suppliers and subcontractors handled these problems and explored their efforts. I found a potential solution while I was examining a gas turbine for my power plant project at one of my suppliers, General Electric (GE). After speaking to its data scientist, I learned about the application of data collection and analytics to the turbine. The sensors were installed to collect real-time data, which enabled the data scientist to remotely monitor the equipment's performance from a centralized data center and improve its efficiency by applying analytical solution to optimize the turbine's system. Based on this encounter with the company's smart features, I began exploring the potency of data science. The connection between data and machine and the utilization of valuable information derived using analytical data was an innovation that could help me revolutionize my analytical methods. Once I realized that data science is the key to overcoming my current analytical limitations, I became determined to learn more about statistics, mathematics, and computer science to attain more sophisticated quantitative and analytical techniques such as statistical analysis, machine learning, optimization and algorithms. It is for these academic goals that I now aspire to pursue a graduate degree in data science.
What intrigues me most about
this field is the concept of data discovery, namely, discovering insights and applying data science to develop data based products, services, or features. These skills enable data scientists to not only support businesses by assisting with management-level decisions that help the business run efficiently, but also by offering new products or features that enhance the user's experience, and generate new channels for profits. LinkedIn'sPeople You May Know feature, which provides users with a list of people it thinks the user is likely to know, is an example of data product I aspire to develop. I find the concept of data discovery especially fascinating because I realized during my work that there is no position at eTEC that performs both a supporting role and is directly involved with developing products; instead, each of these tasks is strictly divided between engineers who designed structures and personnel like myself who supported their endeavors by implementing cost control measures and streamlining material procurement. As a data scientist, I could take on both roles, allowing me to make greater contributions to the business by not only reducing costs, but also creating new lines of revenue through product development, which is the type of work that I hope to focus on during my career. Therefore, while pursuing my degree in data science, I would like to concentrate on learning and researching methods to incorporate statistical, mathematical, and computer-based skills that would optimize the decision-making process and business operation efficiency, and lead to creative ideas to develop viable data-based products.
Realizing programming is one
of the key elements for my academic and career goals, I learned the principles of Java programming from UCLA Extension and participated in a 6 month full-time IT training program offered by the Korean government through Soldesk, a government sponsored IT educational institution. During this program, I learned how to construct complex algorithms, and how to use SQL to store, query and manipulate data by gaining hands-on experience in Java, JSP, Android Studio, R, Linux, Oracle SQL andMySQL as well as completingtwoteamprojects. For one of the projects, I came up with the idea to create an application I had imagined as an undergraduate.During this time, I was highly conscious of the need to use my time productively.Therefore, when I started recording how long I spent doing my work every day, I was surprised to learn I was allocating my time inefficiently by dedicating too much time to one task. In addition, I was spending much less time than I expected on the work at hand because of continuous interruptions, such as phone calls and texts.This event made me realize there would be many other people who are also unaware of how they were spending their time. As a result, I used my experience to design anoutline for a mobileapp that helps users improve their time management skills by trackingthe amount of time they spendon eachtype oftask. While developing the app, our team took sincere care to help each other improve and solve problems that arose. Sunmin, one of the four team members, made many syntax errors such as misspelled name of variables or omitted part of some commands. It took him hours to find the errors within hundreds of lines of source code, making him very stressed out. To assist him with focusing on the more important tasks, I helped him correct any errors and save time. In return, Sunmin taught me his efficient programming style that streamlined my codes. This project was a very important opportunity because it allowed me to demonstrate creativity and teamwork, while simultaneously applying the programming skills I had learned to create software that helps people solve a problem, which in this case is time management.
All of the programming studie
s, which are built upon the quantitative and analytical skills I had developed during my previous work and undergraduate studies in economics, have helped me equip myself with the essential tools I will need to succeed in my higher education at Stanford. In addition,I am currently taking"Linear Algebra and Differential Equations"course to better prepare myself. Stanford's data science track is the optimal road map for me because it leads to the Annual Industrial Affiliates Conference. This annual event, which attracts leading industries from around the globe, will give me the opportunity to better understand various approaches corporations take towards data science, what they hope to gain from it, and how they expect them to be applied. In the end, I will be able to connect with companies that find my career goal in line with their vision for data science. Furthermore, I look forward to being exposed to the work of leading experts through Stanford's statistics, probability and data science seminars to learn about their latest findings and reflecting them in my studies. These experiences will be invaluable to achieving my career goals and help me to prepare for my transition.
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