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University of Michigan School of Information


Faces of UMSI: Yi Mao

Yi Mao sitting on a tree overlooking the beach

Yi Mao was working as a healthcare program evaluation specialist, and found herself frustrated with the inefficiencies built into the processes. She decided to pursue a degree in data science to find ways to improve patient outcomes and reduce costs. With a baby on the way, Yi knew she needed to find a program with the flexibility to balance life, career and education. She found the University of Michigan School of Information Master of Applied Data Science program to be the perfect fit.


Tell us a little about yourself.

I am currently living in Michigan with my husband and our 4-year-old son. I graduated from the University of Michigan School of Public Health in 2013. I worked as a program evaluation specialist in the field of healthcare policy and care delivery transformation at the time when I was enrolled in MADS. In the second year of the MADS program, I was very lucky to land a job opportunity with a healthcare insurance company in Michigan during the UMSI Winter Career Fair and started to work on some predictive modeling. After over a year in this position, I completed all MADS courses.  Meanwhile, I was able to find a data scientist II position with the nation's largest health insurer at the same time. Now I am working on some machine learning models to predict member outcomes.

How did you first hear about the MADS program? What made you decide to enroll?  

When I was applying to programs, I only looked into online data science programs since I was working a full-time job and expecting a baby. I needed to balance parenting, work and school. MADS provides more flexibility than any other programs as each course is 4 weeks long so I can complete the program at my own pace. In addition, MADS curriculum is one of the best. It covers basic programming skills such as Python/SQL databases as well as a wide range of hot topics on machine learning. The other thing is that I noticed the program was looking for nontraditional backgrounds. I have a non-tech background, so I thought MADS would be a good fit.

What is it about applied data science that interests you? How do you plan to use this knowledge? 

After years of working in the healthcare industry, I saw how inefficient the system is. I would like to use data science to improve patient outcomes and reduce costs. I became interested in how to use applied data science to solve problems in the healthcare industry. For instance, one application would be how to identify high-risk patients and take early intervention to avoid ER visits. 

Have you taken other online courses? How does the MADS program compare? 

I took some basic python courses on Coursera, which is the same platform MADS uses. That provided a smooth transition to the MADS program.

How far along are you in the program? When do you expect to get your degree? 

I completed the program in 36 months, from January 2020 to November 2022.

Tell us about the ways you’ve been able to cultivate community among your peers and instructors. 

There are plenty of opportunities to get in touch with peers or professors through Slack channels and projects. We also have a group chat for folks located in Michigan. I met one of my classmates in person who lives 15 minutes away from me. We became good friends and talked a lot about schoolwork and careers.

If you’re currently employed, how are you balancing school with work and home life? 

I only took one course each month. I have been working from home since COVID, which saved me commuting time which I used for school. I also spent a lot of time on homework after my son went to bed on weekdays. And for some lectures with no requirement of watching (such as interviews with industry experts), I listened to the audio when I was driving, which is more interesting than any podcast.

Are there any projects (either at work or other activities) where you have been able to apply or benefited from what you’ve learned in your MADS courses? 

I did one project on premature EDA and two projects on real estate price prediction models. I’ve applied visualization, coding and statistical testing skills from the premature project in some evaluation work I am doing right now. In addition, I used all predictive models from my school project in my current work as I am working with predictive models which go into production.

Is there anything about the MADS program that has surprised you? 

The wide range of topics. The program covers a lot of cutting-edge techniques. In addition, as online students, we are treated like on-campus students. The faculty are very passionate and engaged. I can see how they value and love the program. 

Besides the program itself, I also received support for careers service and was able to find my first data science job via the UMSI Winter Career Fair.

Can you tell us something unexpected about you? 

I am very passionate about the real estate industry, and I used MADS to grow my interest. For instance, one of my MADS milestone projects was to use big data and machine learning to predict property prices in the Ann Arbor area. For the capstone project, I trained a model to predict Airbnb prices in New York City. I have also applied plenty of data analysis and data science skills to help people around me negotiate in real estate transactions and to identify investment opportunities.