Machine Learning Scientist, Personalization

Who We Are 

Wayfair Science powers automation and decision support across all Wayfair business units. Our algorithms tackle a varied and 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 and diverse assortment of home goods. 

The Search & Recommendations Applied Science team is looking for an individual to expand upon our industry-leading recommendations platform and content personalization engine to maximize Customer Lifetime Value using the wealth of data we have about our customers and their preferences. Wayfair’s Recommendations team provides the core platforms and services that allow our customers to discover and buy the products they love by serving the right content to every customer on every touchpoint. Our systems leverage Wayfair’s extensive customer and product data to deliver trusted and valuable recommendations and results in real-time using custom machine learning models. Our mission-critical services are called over a billion times a day. Recommendations are a core competency for Wayfair and a high-priority lever we’re using to drive outsized growth, customer value, and profitability.

In this role, you’ll partner with fellow applied scientists, engineers, analysts, and product managers to bring our next-generation personalization models to life. This is an exciting opportunity to join a growing team with a tangible impact on the performance of Wayfair overall. You will directly impact and drive forward key business initiatives. Above all, you’ll get to work on problems that are both intellectually-challenging and drive real, measurable impact through our online A/B test platform. 

 

Candidates for this position may be based in Boston, MA or Mountain View, CA and will be expected to comply with their team’s hybrid work schedule requirements.

 

What You’ll Do 

• Develop quantitative models, leveraging machine learning and advanced data analysis techniques.
• Own the full machine learning life-cycle from conception to prototyping, testing, deploying and measuring its overall business value.
• Coordinate, prepare, launch and assess live experiments in order to measure the incremental impact of your own work and/or the work of partner teams.
• Uncover deep insights hidden in our vast repository of raw data and provide tactical guidance on how to act on findings.
• Drive adoption and utilization of your products across the organization in ways that drive real business value.
• Architect and help define the required technical platforms that enable us to produce models at scale. 
• Work closely with engineering counterparts to identify and propose solutions to infrastructure limitations.
• Leverage Wayfair’s proprietary data set to scope challenges and opportunities.
• Work closely with Engineering partners to help bring models into production that satisfy specific SLA requirements. 
• Innovate with new approaches, staying abreast of current research in the recommendations field and the broader machine-learning community.

 

What You'll Need

• Machine Learning experience in a professional or advanced academic setting.
• Deep understanding of machine learning frameworks and methodologies such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, Transformers, Graph neural networks, etc.
• Ability to effectively partner with cross-functional leads: strong communication skills, ability to synthesize conclusions for non-technical partners and a desire to influence business decisions.
• Ability to thrive in a dynamic environment where Data Science and Machine Learning plays a key role in shaping business & technical priorities.
• High comfort level with Python.
• Pragmatic approach to problem solving.
• MS or PhD  in a quantitative or related field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.) or equivalent work experience.

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.

If you are having any difficulty submitting your application, please reach out to our careers team at careers@wayfair.com.

We are interested in retaining your data for a period of 12 months to consider you for suitable positions within Wayfair. Your personal data is processed in accordance with our Candidate Privacy Notice (which can found here: https://www.wayfair.com/careers/privacy). If you have any questions regarding our processing of your personal data, please contact us at dataprotectionofficer@wayfair.com. If you would rather not have us retain your data please contact us anytime at dataprotectionofficer@wayfair.com.