What We Do

We create model driven experiments to drive business impact. Check out our blog to learn about ongoing projects!

Our Data

4

Terabytes of Data Captured Daily

3

Billion Google Ads per Month

8

Full Years of Clickstream Data

22.5

Million Tagged and Classified Images

14

Million Products in Catalogue

25

Million Customer Reviews

Our Teams

Merchandising
Personalization & Recommendations
Pricing
Marketing
ML Systems Engineering
Operations Research
Computer Vision
Data Science EU

Our Blog

TopShelf: How to Arrange a Page of Products, Not Just Rank Them in a List

May 5, 2020

Many approaches to ranking a list of products or search results are based on assigning a score to each item and sorting in descending order—in other words, greedy sorting approaches. In e-commerce, predictive models place the product that the custo...

The Visual Complements Model (ViCs): Complementary Product Recommendations From Visual Cues

March 16, 2020

Introduction Creating a recommendation system for home decoration poses unique challenges: each customer has his/her own taste and would like to maintain a cohesive personal style across his/her home. We at Wayfair know that it is hard to describe t...

Hoover: How to enable data scientists to stop managing ETL pipelines and get back to doing data science

February 11, 2020

Summary Business moves fast and data science runways are long. What can we do to remove friction and iterate on data science models as quickly as possible? In this blog post, we describe how Wayfair builds Jupyter-based tooling that empowers data sc...

Who We Are

We are a diverse group of analytical problem solvers. And we might be more than a little nerdy.

31

ACADEMIC DISCIPLINES

22

NATIONALITIES

62

PHDs

100+

DELIGHTFUL NERDS

Our Leaders

Dan Wulin

Director of Data Science

PhD Physics

University of Chicago

Corey Gilbertson

Head of Pricing

BA Economics

Hamilton College

Tulia Plumettaz

Head of DS Merchandising

PhD Operations Research

Columbia University

Anvesh Sati

Head of DS Marketing

MBA Finance & Entrepreneurship

Babson College

Sunanda Parthasarathy

Head of Personalization & Recommendations

PhD Physics

Purdue University

Jae-Woo Choi

Head of Computer Vision

PhD Electrical Engineering

Caltech

Susan O’Dell

Head of Operations Research

MS Operations Research

MIT

Franklyn Tamalenus

Head of ML Systems Engineering

MBA Marketing & E-Commerce

University of Rochester

Benjamin Schroeder

Head of Data Science EU

PhD History

Humboldt University of Berlin

How We Work

Here at Wayfair Data Science, our core values are rigor, curiosity, and fun.

Rigor

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.

Curiosity

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.

Fun

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.