Associate Director, Data Science - Personalization
San Francisco, CA
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 Data Science leader to head the personalization of Wayfair’s product recommendations. In this role, you’ll be part of the Search & Recommendations leadership. You’ll lead a team of data scientists and machine-learning engineers, leveraging customer behavior and product data to create a tailored customer experience. You’ll own crafting a research agenda and ensuring its execution, constantly improving on the current status quo of our personalization models, and you’ll partner closely with leaders on engineering, analytics, and product management to bring our next generation personalization models to life. Your work will be far reaching, supporting recommendations across our storefront, email, and marketing channels, serving billions of recommendations each day.
What You’ll Do
- Lead a team of 5-10 experienced Data Scientists to research & productionize state-of-the-art personalization solutions
- Leverage Wayfair’s proprietary data set to scope challenges and opportunities
- Collaborate closely with Product, Analytics, and Engineering partners to translate business asks into technical solutions
- Innovate with new approaches, staying abreast of current research in the recommendations field and the broader machine-learning community
- Architect and help define the required technical platforms that enable us to produce models at scale
- Provide partnership within Wayfair’s Search & Recommendations leadership
What You’ll Need
- 7+ years of experience in a research-oriented quantitative or technical work environment, and advanced degree (PhD) in a quantitative field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.)
- 3+ years experience managing a technical team driving scalable solutions
- Ability to effectively work with business leads: ability to synthesize conclusions for non-experts and desire to influence business decisions
- High comfort level with Python (preferred), or with other languages such as Java, C#, etc., and with big-data technologies such as BigQuery or Spark
- Machine Learning experience (such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, NLP, etc.), and familiarity with recommender systems
- 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.