Senior Data Scientist, Data Science Recommendations

Who We Are

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. 

The Data Science Search & Recommendations team is looking for an experienced Senior Data Scientist 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 data scientists, engineers, analysts, and product managers to bring our next-generation personalization models to life. You’ll spend one part of your day reading white papers and the other part of your day implementing them. You’ll test and explore state-of-the-art deep learning architectures on terabytes of data. You’’ explore reinforcement learning approaches for generating recommendations for customers across multiple channels. You’ll explore how to evaluate and de-bias recommender systems offline. The models you develop will have tremendous business impact, directly measurable through our online A/B test platform.

What You’ll Do

• Partner closely with marketing peers to develop personalization strategies tailored for email touchpoints
• 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

• 4+ years of experience in a quantitative or technical work environment with BS/MS or advanced degree (PhD) in a quantitative field (e.g. statistics, mathematics, economics, computer science, physics, neuroscience, operations research, etc.)
• 5-10 years of experience in a corporate, start-up, or research environment
• 3+ years experience with advanced programming languages and big data/ distributed system tools like Python, R, Scala, Java, Hive, SQL, Spark, etc
• 3+ years of professional machine learning experience (such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, NLP, etc.), and familiarity with recommender systems
• Ability to effectively work with high-level business stakeholders: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions
• An analytical, creative, and innovative approach to solving difficult problems
• Intellectual curiosity and a desire to always be learning!

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.