What We Do
We create model driven experiments to drive business impact. Check out our blog to learn about ongoing projects!
Terabytes of Data Captured Daily
Billion Google Ads per Month
Full Years of Clickstream Data
Million Tagged and Classified Images
Million Products in Catalogue
Million Customer Reviews
Personalization & Recommendations
ML Systems Engineering
Data Science EU
Gemini: Wayfair’s advanced marketing test design and measurement platform
July 8, 2019
At Wayfair, data scientists help optimize our marketing channel performance by rapidly and iteratively developing machine learning algorithms and data-driven strategies. When it comes to measuring model efficacy, AB testing plays a central role and s...
Wayfair DS Explains It All: Jinnie Chen on Product Tagging
June 24, 2019
Product tags reveals the detailed characteristics of a product which can be used to power PDP (product display page) creation, searching, filter creation and more.This week in Wayfair Data Science’s explainer series, Senior Data Scientist Jinnie Ch...
Creating the “Superclass”: Improving object detection at Wayfair via product class clustering
June 14, 2019
Executive Summary Object detection is an important component of the computer vision workflow at Wayfair. The goal of object detection is to detect bounding boxes of the objects in an image along with the class information (see feature image above), ...
Who We Are
We are a diverse group of analytical problem solvers. And we might be more than a little nerdy.
Director of Data Science
University of Chicago
Head of Pricing
Head of DS Merchandising
PhD Operations Research
Head of DS Marketing
MBA Finance & Entrepreneurship
Head of Personalization & Recommendations
Head of Computer Vision
PhD Electrical Engineering
Head of Operations Research
MS Operations Research
Head of ML Systems Engineering
MBA Marketing & E-Commerce
University of Rochester
Head of Data Science EU
Humboldt University of Berlin
How We Work
Here at Wayfair Data Science, our core values are rigor, curiosity, and fun.
From search engines to shipping logistics, Data Science is central to everything we do at Wayfair. As such, it's vital that we get things right. Our thorough in-house testing platform, rolling code deployments, and iterative research-style approach ensure that our work is thorough, precise, and driving the business.
Wayfair’s abundance of data means that there are always new problems to be solved. As such, team members are empowered to explore our data to develop new, high impact ideas and then develop experiments to probe those questions. We also partner with professors and students from Harvard, MIT, Stanford, Columbia, and Cornell to bring the most advanced ML technologies into production.
No one is too busy to brainstorm or answer a question, and code is shared as freely as the snacks in the kitchen. We like doing things together, whether that means collaborating on a pricing experiment or going rockclimbing, kayaking, painting, or visiting a distillery with our coworkers during our monthly pod outings.