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Meet Charles Qian: The Fast Interview

Charles Qian, lead data scientist at Fast, with his family

Charles Qian

Role: Lead Data Scientist - Consumer

Team: Data Science & Analytics

What do you do at Fast? 

I think about how consumer data can help Fast to understand our users better. Conversely, I also think about how to improve our product through data so our users are happy. 

Describe your typical day at Fast.

We set up hypotheses about consumer behavior, and break it down into several pieces to perform statistical analysis. We also build data pipelines and develop data visualization tools to help non-technical audiences to digest data fast and efficiently. 

Where were you before Fast?

Data scientist at Wish for about three years. Before that, I was a quantitative analyst at Bank of America for two years.

Why did you say yes to Fast?

After Wish’s IPO in December 2020, I asked myself where my next adventure would be. I had a conversation with my current manager, Rudy (Zen, Director of Product Management at Fast) about the unique opportunity to build Fast data from 0 to 1, and the data-driven culture at Fast. 

Where did you grow up, and what were you like as a kid?

Shanghai, China. Both my grandparents are professors in chemistry at Fudan University, and I was very curious about everything in their labs.

What led you to data science?

Nowadays when we talk about business decisions, it is easy to have a hypothesis in your mind right away, but it is hard to validate it, especially how can we quantitatively validate it? Here is how data science can help. Furthermore, most of the time we cannot even make a hypothesis, and data can help you to get insights. It is that trigger that led me to the world of data science, along with my childhood curiosity.

What was your first job?

Data analyst internship in American Standard in 2010, which influenced my decision to go to graduate school to study advanced statistics.

What are your fellow Fast data scientists doing that stands out?

Every data scientist at Fast is extremely results-oriented. We collaborate as a squad with software engineers, designers, product managers, data engineers/scientists. We are open to everyone’s voice, and help each other.

Proudest moment as a data scientist?

I taught an online course on statistics and A/B testing, which helped many students to successfully find their dream jobs as data analysts or data scientists.

Favorite thing about being a data scientist?

Problem solving. As a data scientist, you don’t focus on one specific area since different problems have different ways to solve. You can solve this question with a simple method, but the next one may require a very sophisticated modeling technique. 

Morning person or night owl?

Night owl, but I’m trying to be a morning person.

What’s something you regularly do, but know you shouldn't?

I stay up too late sometimes.

Advice for data scientists wondering what to do next?

Don’t stay in your comfort zone – always explore new data tools and/or new techniques to solve problems. 

Where can we follow you?


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