Leadership, Data Science Catalog

Key Skills

Java Programming, Python Programming, SQL, Data science techniques

Job Description

This is a leadership position in an applied science role to develop foundational capabilities for Wayfair:

1) Understanding the relationship between product information across text and image modalities: product-content similarity

2) Predict product substitutability before a product enters our catalog: day zero substitutability

3) Build feedback loops from our customers to discover and exploit substitution in our catalog: marketplace substitutability

 Optimizing these capabilities for the complexity of information about our products, the breadth and diversity of our catalog, in a way that supports Wayfair's global growth, pose key challenges. Further, product substitutability is difficult and potentially costly to measure as our products are not commodity goods that are repeatedly purchased (e.g. the customer needs the perfect sofa for their living room). We build generalized, unified models in the form of rich, concise representations to address these challenges and power decision making across Wayfair. These are used as i) features for other science models predicting customer engagement with our products, ii) through scalable search systems for discovering exact or substitutes across our catalog or our competitors', and iii) validation of substitution to drive end-to-end efficiency in product sourcing, on-site recommendations, and distribution.

What You’ll Do

• Provide technical leadership in the development of state-of-the-art deep learning models that unify image and text similarity understanding, and predict substitutability from product information and customer feedback. 
• Work at scale in the cloud to develop and deploy representation models using billion-scale datasets of images, text blobs, products, and user interactions
• Setup offshore human-in-the-loop experiments and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. 
• Collaborate with other science leaders to develop shared strategies for efficiently discovering substitution opportunities through customer feedback loops that are exploited within our marketplace and operations.
• Keep abreast of relevant research in search query, information retrieval, and relevance ranking. Maintain expert knowledge in computer science, machine and deep learning, data mining, natural language processing, active learning, large-scale optimization techniques and more. 
• Engage in broader strategy and execution discussions in the Data Science Organization, providing input from your program experiences to enhance our priorities across the board. 
• Work with cross-functional teams of product managers, engineers, scientists, and analysts, to design implementation and experimentation strategies. 
• Actively contribute to the wider data science and machine-learning community by sharing and publishing your findings within Wayfair and through collaborations.