Welcoming Data Scientist Christopher Peters to Zapier

Christopher Peters
Christopher Peters / Published April 21, 2014

A note from Wade Foster, Zapier CEO: Finding new teammates for an early stage startup is tough. It's about identifying just the right mix of skill and culture fit. This has never been more evident than with our latest hire to fill a new data position. After interviewing 50-plus people with backgrounds in statistics, data science and data engineering, Chris Peters stood head and shoulders above the rest.

What will a data scientist do at Zapier? Chris brings expertise to the table that will help the team increase the reliability of all apps on Zapier. He'll also help personalize the app experience for you, making it easier to find apps and integrations that fit your exact needs. And that's just some of immediate tasks on his plate. Without further ado, a warm Zapier welcome to Chris!

Within three hours of starting my job at Zapier, I began to better understand the crazy hard and crucial problem this team of 10 people is trying to solve. If you’re a professional today, you probably know the problem, too: the number of apps you’re using is growing, and your data is becoming more and more dispersed. As a result, you need those apps to talk to each other.

Having the chance to work on this problem in an engineering role is really exciting! When Mike Knoop, one of Zapier’s co-founders, reached out earlier this year and introduced me to a few of the complexities, my mind raced with the possible ways statistics could be of help.

So here I am, Zapier’s first data scientist, a hybrid position of a statistician and software engineer. On a daily basis, data scientists set up data collection to make sure important metrics are being collected. They also clean, organize, and finally analyze data to extract business insights. Another fun aspect of the job is building algorithms that can provide a custom web application experience, something I hope to use to improve Zap recommendations for customers.

Before Zapier

My background is in statistics and data science and Zapier is my second startup gig. I previously worked as a data scientist and developer at Treehouse, a company whose mission is to teach the world to code. There, I helped guide the user interface design and product fit with experimentation—measuring user activity and learning was an important part of my job.

Treehouse graciously funded the second half of my education in pursuit of a master’s in applied statistics degree from Louisiana State University (Geaux Tigers!). It was at LSU that I was first introduced to statistics in the form of econometrics. I was hooked.

At Zapier

Zapier is solving a critical Internet infrastructure problem. As the number of apps increases, the number of connections made app-to-app increases exponentially. With a hub at the center like Zapier, that same number increases linearly.

Zapier hub and spoke

Taken a bit further, the magnitude of the problem becomes clearer. Even as apps integrate themselves, the potential for reliability problems, code reading / development requirements, all of these costly problems explode.

With that in mind, there are a few key ways that I hope to add value for all of Zapier’s customers. First, I’ll be working with engineers to install a statistically-driven reliability system. This will let us proactively improve API connections and work with API owners to create the most reliable connections possible.

Another priority of mine is use case discovery. I want Zapier to be a go-to source for small business efficiency. If we can save businesses the time it takes to identify the most useful Zaps for them, they can more quickly set up automation and get back to doing what they do best—their business.

Data Science Example
An example of exploring Zapier use cases (labels hidden) with data science.

Finally, I’ll be working with Bryan Landers, our product designer, to improve and polish the user interface. I have a specific interest in giving power users what they need when they need it, while keeping the rest of the app digestible for those less familiar with how Zapier works. With survival analysis tools and A/B testing, we’ll actually be able to measure user interface confusion faced by Zapier’s customers (and then reduce it).

I want Zapier to be your go-to interface for apps. Why use 20 when you can use one?

At Treehouse I learned that trying many new things can pay off, if it’s done carefully. I’m really happy to join the Zapier team and help make a better product that I think solves a real problem.

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