Yufei Qin, Data Services Specialist: Q&A

Yufei Qin

Yufei Qin joined the Princeton University Library (PUL) as a Data Services Specialist in August 2022. Before PUL, she graduated with a master's degree in Social Policy and Data Analytics at the University of Pennsylvania. She also holds a bachelor's degree in Financial Mathematics from the University of Liverpool in England and Xi’an Jiaotong Liverpool University in Suzhou, China. In addition to her master's from UPenn, Yufei is earning a master's degree from Georgia Institute of Technology.  

What is your role as Data Services Specialist and what field(s) do you specialize in? 

Data Services Specialists provide guidance, instruction, and consultation on quantitative research methods and statistical software for Princeton students, faculty members, and researchers in various disciplines in social sciences, including economics, politics, public policy, psychology, sociology, etc.  

We provide methodology guides and statistical software hands-on instructions through one-on-one consultations, library guides, and workshops. The software includes R, Stata, MATLAB, SPSS, Excel, and sometimes python. We try to keep up with the most cutting-edge methods, software packages, and software in the area, as the students and researchers at Princeton are always keen to learn new ideas and new approaches. 

What interests you about working with data?  

Data is a fascinating new language, and we are still at the primary stage of understanding and exploring it. Data itself is open to various interpretations so it can be both so powerful and powerless at the same time. That’s what makes it so interesting.  

With credible methodology, data is a powerful tool that helps us understand the world we are living in. Data can be used to tell the stories that we already believe, like how the hour you spent studying is positively correlated to your study results. It can also help us visualize disparities, such as the size of the gender pay gap.  

That said, we must be careful to not reduce everything to a measurement. People tend to believe that data is objective and convincing, but that’s not always the case. Some agencies, for example, have used data to predict the possibility of recidivism, causing too many false positives and reinforcing historical biases.  

Additionally, being a data consultant allows me to communicate with wonderful students and scholars on a one-on-one basis. It’s so exciting to work with so many energetic minds that crave new knowledge and improvement.  

Could you tell us about some of your work? 

When I was in London, I worked with the Egyptian office to design a better Bonus-Malus System for car insurance pricing. While earning my master’s degree, I took an interest in finding out the flaw (bias) of machine learning technology applications in the welfare system. For example, Michigan once adopted a system called Midas (Michigan Integrated Data Automated System), which determined the eligibility of people collecting welfare and unemployment benefits. It remains a complicated measure to avoid the historical bias incorporated in the previous data, which the ‘machine’ used to ‘learn’. 

How do you hope to support members of the Princeton University community? 

Princeton researchers and students are full of inspiration. They are never afraid of challenges and always ready to learn. Also, it’s fun just talking to them. After the hit of the pandemic, it made me realize that human interaction is so valuable, especially with the trend that we use devices to communicate more and more. I believe that as a data specialist working in the Library, not only can we provide our knowledge and service, but we can also actively engage with the community to create a diverse, inclusive, and warm atmosphere for everyone. 

Questions? Contact Yufei via email at yq9378@princeton.edu  

Published on January 24, 2023