: Data Scientist, Storefront Recommendations

Data Scientist, Storefront Recommendations

Boston, MA

Wayfairs Data Science team builds the algorithmic systems that drive our business.

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 Storefront Recommendations team is looking for a Data Scientist to focus on leveraging customer behavior and product attributes to personalize the Wayfair customer experience. In this role, youll partner with fellow data scientists, engineers, analysts, and product managers to bring our next generation recommender and ranking models to life. Youll spend one part of your day reading white papers and the other part of your day implementing them. The models you develop will have tremendous business impact, directly measurable through our online A/B test platform. 

 

What You'll Do

  • Own the full Data Science life-cycle from conception to prototyping, testing, deploying, and measuring its overall business value
  • Develop quantitative models, leveraging machine learning and advanced data analysis techniques to create novel solutions to complex business problems
  • Integrate your algorithmic solutions into our technical platforms to run at scale and directly change the experiences of customers on our site
  • Drive measurable business value collaborating with business teams to change the course of Wayfair
  • Uncover deep insights hidden in our vast repository of raw data, and provide tactical guidance on how to act on findings
  • Use data to improve the decision-making of our employees, and ultimately, to enhance the experience of our customers and our suppliers
  • Work with a team of friendly and motivated scientists working together to build novel solutions to business problems

 

What You'll Need

  • Recently completed Ph.D  in a quantitative field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.) OR an advanced quantitative degree and at least 2 years of experience
  • An affinity for data along with experience leveraging statistics and regression analysis is a plus.
  • Experience with or an interest and ability to quickly learn SQL and Hadoop.
  • Experience with or interest and ability to quickly pick-up programming skills relevant to data science such as Python and R.
  • Quick learner with an analytical approach to solving problems as part of a team who has good communication skills.
  • Must be a hard worker who enjoys solving challenging problems in a fast-paced environment.

 

About Us:

Wayfair is one of the worlds 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, were 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 youre looking for rapid growth, constant learning, and dynamic challenges, then youll find that amazing career opportunities are knocking.

No matter who you are, Wayfair is a place you can call home. Were 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. Thats why were 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.




Full-time