This is a hybrid role located at Wayfair’s Boston, MA or Mountain View, CA Office. Required in-office 3 days per week.

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. It also allows our suppliers to surface their products to the right customer to showcase their inventory and build their brand.

The Product Recommendations team is searching for a Data Science/Machine learning scientist to join our sort optimization team. This team works on multi-objective optimizations which strike the balance of showing popular products and showcasing sponsored products or brand-aware display ads in the product search and recommendations. In this role, you’ll partner with fellow engineers, analysts, and product managers 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.
• Own the full Data Science 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 & 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

• Recently completed PhD  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.
• 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 plays a key role in shaping business & technical priorities.
• Machine Learning experience in a professional or advanced academic setting (e.g., supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, etc.)
• High comfort level with Python (preferred) or with other programming languages.
• Experience with big data tools such as Hadoop, Spark, Presto, etc.
• Prior experience building scalable data processing pipelines with big data tools such as BigQuery, Spark, etc.
• Experience with Airflow and containerization (Docker) are nice to have
• Experience with multi-objective optimization is a bonus.
• Intellectual curiosity and a desire to always be learning!