ML Scientist II

Who we are

Wayfair is moving the world so that anyone can live in a home they love – a journey enabled by more than 3,000 Wayfair engineers and a data-centric culture. The Search, Marketing, and Recommendations technology science team (SMART) builds and owns all the Machine learning (ML) products that power all search, marketing, and recommendations technology across Wayfair. 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, to driving marketing experiences customers love all at web scale. 

We are looking for machine-learning scientists for R&D of the ML systems that power our real-time Search type-ahead, content recommendations, and algorithmic customer understanding experience. In this role, you’ll partner with fellow scientists, engineers, analysts, and product managers to apply science and machine learning skills to directly impact Wayfair’s revenue. 

What you’ll do

• Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers
• Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions
• Collaborate closely with various engineering, infrastructure, and ML platform teams to ensure adoption of best-practices in how we build and deploy scalable ML services
• Identify new opportunities and insights from the data (where can the models be improved? what is the projected ROI of a proposed modification?)
• Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.

What you’ll need

• Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, or related field.
• 6-9 years of industry experience in developing machine learning algorithms 
• Proficiency in Python or one other high-level programming language 
• Solid hands-on expertise deploying machine learning solutions into production

• Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, etc. 

• Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity 
• Intellectual curiosity and enthusiastic about continuous learning

Nice to have

• Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)
• Familiarity with GCP (or AWS, Azure), ML model development frameworks, ML orchestration tools (Airflow, Kubeflow or MLFlow)
• Experience in information retrieval, query/intent understanding, search ranking, recommender systems etc. 
• Experience with deep learning frameworks like PyTorch, Tensorflow, etc.