Wayfair Data Science powers automation & decision support across all Wayfair business units. Our algorithms tackle a varied & broad spectrum of challenges in the Wayfair marketplace; from empowering suppliers to easily add products to our catalog, to enabling our customers to discover and purchase a vast & diverse assortment of home goods.
Wayfair Professional’s (B2B) mission is to help businesses make good spaces great. We leverage Wayfair’s platform to serve professional customers in many industries, including Interior Design, Commercial Office, Contractor, Property Management, Accommodations, Foodservice and Education, with cross-functional teams focused on improving the customer experience in each target vertical.
The Data Science Tech Lead role within the B2B Science team at Wayfair will develop and deploy machine learning models that power algorithmic decision-making across the business, while leading the team by mentoring other scientists.
Data is at the heart of everything we do and Data Science + ML engineering is crucial to our ability to scale as we train and deploy the next generation of ML products at Wayfair that power the way millions of customers interact with us. You will be processing petabytes of un/structured first party and third party data and building scalable modeling pipelines that help us evaluate the long-term value of the millions of products we offer and of actions the business can take. The tools we’ve built thus far and the new capabilities we have on our roadmap aim to redefine how we think about model development, deployment, and monitoring.
Above all, you’ll get to work on problems that are both intellectually challenging and drive real, measurable impact, first and foremost, for our customers - and as a result for Wayfair at large. To get a better sense of the type of projects we work on, check out our Data Science & Machine Learning blog posts here!
What You'll Do
- Build machine learning models to drive algorithm decision making across Marketing, Sales, Operations & Pricing domains for Wayfair Professional
- Build highly scalable distributed data processing platforms that evaluate the long-term incremental value of our millions of offerings and of actions that the business can take
- Collaborate with other data scientists to build high quality ML models that can robustly scale up to large volumes in production
- Partner closely with various business & engineering teams to drive the integration of our model outputs & algorithmic decision-making systems into existing production systems
- Be a builder of tools, software, and microservices that enhance or streamline various steps or challenges within the data science workflow & our tech stack
- Extend existing ML libraries and frameworks for scalable model training & deployment
- Own the full data science life cycle: scoping to prototyping, testing, deploying, measuring value and iterating
- Identify and innovate new opportunities to drive business results through data science
What You'll Need
- BS in computer science (or equivalent degree) and 4+ years of experience in a quantitative field (statistics, mathematics, economics, operations research, physics, neuroscience etc), data engineering, data science, or software development, or PhD or MS in computer science (or equivalent degree) and 2+ years experience
- Proficient at one or more programming languages, e.g. Python, R, etc.
- Comfortable with SQL and ability to wrangle data from various sources
- Proficient in parallel computing and big data technologies, particularly Hadoop, Hive, Spark.
- Commercial experience in production-environment-driven ML design
- Thorough command of general data science and machine learning techniques, good understanding of data engineering practices
- Experience with any of: GCP, Kubernetes, Docker, Snowflake
- Communication skills that can influence across organizations and at all levels
- Ability to work on cross-functional projects and communicate with stakeholders at multiple levels of technical detail
- Good understanding of experimental and statistical techniques for the design of A/B tests to measure the impact of initiatives
About Wayfair Inc.
Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.