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Jiying Z

- Research Program Mentor

MS at Stanford University


Anything related to data science, machine learning and AI, social sciences, and the arts!


If you're interested in learning to dig out stories from numbers, you've come to the right person! I have been working and learning in the field of statistics and machine learning for the past 5 years. My academic training is in applied statistics, and I have always worked in the data science and biostatistical fields with an emphasis on health applications. My job is all about using the right tools to make data tell you interesting stories, specifically in a social good/healthcare-related setting. It's astonishing how much you can learn from cold, hard data. I believe it is a huge key to understanding the issues, biases, and effectiveness of efforts in the world around us. If this excites you, I can help give you the tools and methodology to start mining into the hidden truths around you, from as far out as addressing nationwide issues to as close to home as your immediate neighborhood. Additionally, I can give mentorship around the soft skills you need to help you succeed no matter what your future goal is!

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Community Analysis:

Is there some issue you've been aching to know more about in your community? For example, what student characteristics contribute to higher academic performance, and how can we help raise performance for the underserved? Is crime rate shifting in some way, and what might be the reasons? Is a local effort creating the impact that it wants? Together we can come up with an interesting topic and conduct a research project from data collection to applying most commonly used statistical techniques, culminating in an article for your school or local newspaper to bring awareness and insight into the issue.

Machine Learning:

The possibilities are endless here. Whether you're interested in creating a song recommendation system for your friends or taking on a Kaggle challenge (that's a well-known machine learning competition platform, by the way), I can help you navigate through all the essentials of building an end-to-end machine learning workflow. You will learn about common issues and nifty ways to tackle them as well!

History of statistics and mathematics:

Each concept in STEM subjects is rich with their very own history. Pick a STEM topic you are interested in (e.g. sampling techniques, or a certain machine learning method you've heard of), and do research into how it came about and what it has developed into now. Extra brownie points if you can identify ways to improve it! Write up your findings into a blog post and share it with the community.

Coding skills

R, Python, SQL,

Languages I know

Mandarin Chinese

Teaching experience

I have mentored previous Polygence students, corporate interns and new hires, and two students through summer mentorship programs at SFASA.


Work experience

Meta (2021 - 2023)
Data Scientist
Genentech (2023 - Current)
Real World Data Scientist
QuantCo (2019 - 2019)
Machine Learning/Quantitative Research Intern
Meta (2020 - 2020)
Data Science Intern


University of California Berkeley (UC Berkeley)
BA Bachelor of Arts (2018)
Stanford University
MS Master of Science (2021)


"Polygence was a great experience for me. Jiying was really prepared in all of the sessions and spread the workload out evenly throughout the 10 weeks so that writing the final report wasn't too overwhelming. During each meeting, I learned about some new aspect of modeling or analyzing data that would advance the project. For homework, Jiying kept the options pretty open. I had the freedom to explore whichever part of the data I was most drawn to, and then we would discuss in the next session. Overall, I had a lot of fun and learned interesting concepts beyond the scope of a typical high school course."


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