Senior Data Scientist - Product Recommendations

Which products, out of millions of options, are customers seeing when they browse our websites? How to dynamically improve product rankings to account for changes in customer behavior?

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 is a core competency for Wayfair and a high priority lever we’re using to drive outsized growth, customer value, and profitability.

The Product Recommendations team is searching for a Senior Data Scientist or Machine Learning Engineer to join our default recommendations team. This team develops the algorithms that power our overall product recommendations, accounting for ~90% of products shown to customers across various placements. An example can be found on our tech blog. In this role, you’ll partner with fellow data scientists, engineers, analysts, and product managers to apply data science and machine learning skills to bring our next generation recommendation platform to life. The ideal candidate enjoys sitting at the boundary of data science and engineering, and is comfortable working with partners across the organization to distill ambiguous business asks into technical plans. 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. 

What You’ll Do 

• Develop quantitative models, leveraging machine learning and advanced data analysis techniques to improve our product recommendations
• Own the full Data Science/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 act on findings
• Drive adoption & 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 

What You'll Need

• 2+ years experience with advanced programming languages and big data/ distributed system tools like Python, R, Scala, Java, Hive, SQL, Spark, etc
• 2+ years of professional machine learning experience (such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, NLP, etc.), and familiarity with recommender systems
• Familiarity with ML model development frameworks, ML orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Python, and SQL.
• Ability to effectively work in a dynamic environment, where there can be degrees of ambiguity, with high-level business stakeholders: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions
• Excellent organizational, analytical, and hypothesis- driven critical thinking skills to identify business opportunities and transform data into actionable insights
• Intellectual curiosity and a desire to always be learning!

Nice to Have

• Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks)
• Experience building innovative recommender systems

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.

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). 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.