Wayfair has over nine million unique items in its catalog, and tens of thousands of new ones are added every day. These products come from 8,000 different suppliers who sometimes sell the exact same products — two completely unrelated suppliers could be buying the exact same area rug… Read more
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… Read more
Earlier this month, the Pricing Algorithms team had a Community Service Hack Day here at our office, dedicating an afternoon to work on simple tools that could be used as part of any project. The day was an opportunity to fill any knowledge gaps in how our team… Read more
As an engineering leader, it can sometimes be a real struggle to make the work of your teams visible, especially in a problem space that doesn’t reside in traditional customer-facing areas. Without that visibility, it can be hard for team members to feel really great about what they’ve… Read more
In April, I attended the Data Science Research Symposium at University of Massachusetts Amherst and gave a short talk highlighting Wayfair’s marketing data science projects. The full video and slides are below, but here’s an overview. Goals of marketing data science at Wayfair As the largest… Read more
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
At Wayfair, the data science teams collaborate with other partner teams to translate business problems into analytical frameworks, leverage data and machine learning to make robust predictions and recommendations, and build engineering architecture to scale up machine learning solutions. In a recent machine learning… Read more
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… Read more
Something we often emphasize on our teams here at Wayfair is that ideas could and should come from everywhere. It is important that every individual, not just our business owners, product managers, and designers, are thinking about our work in the context of the… Read more
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… Read more
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… Read more
