By Yang Fu
I was born in China and my family has passed down the tradition of practicing medicine for generations. I received my Bachelors degree in China from Xiangya School of Medicine which has a long-standing reputation for medical education in China.
My junior year, I had a publication research with a group of doctors. They are excellent in practicing medicine, however, they have no experience in data analytics, so we started the project the way they were familiar with and had been implementing for a long time, which was in my mind, the old-fashioned way, by hiring a secretary to query the data upon our requests. At that time, I felt the method was inefficient and error-prone, but it reminded me of a speech given by a professor from the University of Texas about his research using advanced model technology, so I contacted the professor and he invited me to his lab to see what he was doing.
In Texas, he introduced how he was using modern technology in gene level researches. Although we focused on different levels, his study still offered me great insight into the effect of bringing modern technology into the project. When I returned to China, I talked with the doctors from my team about applying data analytical tools into our research and they showed great interest in this. We asked the secretary to make electronic files instead of paper documents and generalize them into CSV files. After the data preparation phase, we introduced the programs Tableau, R and Python into our project, which highly raised our efficiency and accuracy. The data analytical tools allowed us to finish our work ahead of schedule. This was a turning point for me as I turned my interest from medicine to data science and I became obsessed with it. Since I wanted to learn the analytical tools more comprehensively and systematically, I chose to be here at Michigan State University to continue study.
During my study at MSU, I participated in several projects including a project with the KellyOCG where I built programs with my teammates using R, Python and Tableau to run analyses through millions of rows of data. I realized the power of large data and I had a strong desire to use the skills I learned from class in the business world.
I really appreciate the opportunity Dean has given me to intern at Whittaker Associates. He is not only my boss, but more like a mentor and a friend to me. When I started the job, although I know how to program, I had no idea how to use the programming skills. Dean offered me great insight. In the first three weeks, I built two programs, allowing us to work more efficiently. This summer, my colleague Joe are I are working to develop an algorithm that would allow us to use machine-learning tools for our company to better predict other companies’ behaviors by historical data. I believe this a revolutionary step to continuing to better Whittaker Associates’ accuracy and continue to be a step ahead, using the power of advanced analytic tools.
Although it might be “weird” for some people to see my shift from medicine to data science, I am certain that I am on the right path. In the end, we have to live with our own decisions and no one else can do that for us. As a believer of data science, I am positive that tremendous positive impact will be brought by data science through all industries in the future. It is not that I am ending my family’s tradition but rather, I am creating a new one of my own.