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June 25, 2018
A little over a year ago, I found myself taking on a unique and exciting opportunity: Building a Python Platform team from the ground up. Despite its size, Wayfair gives teams a large degree of autonomy in deciding how they operate, which meant we had a true blank slate to start with. Most of my experience has been on product-oriented teams, and this was my first time leading a platform team with purely internal customers. I want to share that journey with you, but first let me give some context around why we needed this team in the first place.
June 18, 2018
No two people's paths to Wayfair are exactly the same. On our data science team alone we employ physicists, neuroscientists, biophysical chemists, economists, mathematicians, statisticians, and more! Our data scientists are united by a love of data and a knack for problem solving, but each person has a different story to tell about how they gained these skills.
June 1, 2018
Early in 2017, in the course of deciding to convert to React as our frontend framework, we realized we needed to render our React components on the server. We adapted Airbnb’s open source Hypernova renderer for our purposes. In particular, we implemented custom module resolution and modified the Hypernova module loader in order to have complete sandboxing between requests, with much less chance of accidental data leaks.
May 18, 2018
Last year, Wayfair launched Visual Search, a new and novel way to find products on our website. Users can now upload photos of furniture they like and find visually similar matches in an instant. If you need a little refresher on this technology, the original blog post can be found here.
May 8, 2018
Last month, the inaugural React Finland Conference was held on April 24–26 in Helsinki, Finland’s capital. It was the first ever React conference in Finland, and I was lucky enough to present a workshop there on component-driven development. Having React as a framework of choice at Wayfair, this was a great opportunity to share my knowledge as well as pick up some useful learnings from other members of the React community.
May 2, 2018
Since I began my tenure at Wayfair as a data scientist, many PhD students and postdocs have reached out to ask for advice about the transition to data science in industry. After a fruitful collection of conversations, I’ve realized that there are popular misconceptions about what it means to be a data scientist.
April 23, 2018
As data scientists, we face a variety of problem types. One of our critical challenges is identifying the proper methodological approach to solve each problem. By doing this, we avoid force-fitting the wrong tool to solve a problem, and we avoid having to reformulate a question to fit a specific method.
April 17, 2018
As Wayfair has grown and matured its software development and data center operations over the past decade, and particularly over the last five years, we have embraced the principle of providing maximum visibility into our processes and systems. The result is a very large logging and time series infrastructure built to receive a constant stream of application logs and metrics. Our logging infrastructure, built on the Elasticsearch stack, has benefited from continuous improvements from the Elastic company, as well as other resources such as consulting, training, and books. However, Graphite, our time series solution, has been more or less a self-supported system.
April 10, 2018
As Wayfair’s business has scaled, so too has the size of our engineering teams – not to mention the complexity of the software features we’re building. At the same time, moving quickly in the global tech landscape has never mattered more. As a modern tech company, one simply cannot afford to slow down the rate of feature delivery.