Wayfair-posted 4 days ago
Full-time • Mid Level
Hybrid • Boston, MA
5,001-10,000 employees

Who We Are: Wayfair is an online retail platform with the mission to enable everyone to live in a home they love. To do this, Wayfair builds and leverages cutting-edge Machine Learning and AI products. Within the broader Science Org, the Supply Chain and Retail Technology (SCRT) Science team drives growth by tackling fundamental challenges pertaining to supply chain and post-order customer experience; for example, building end-to-end systems to predict delivery dates at different points in the shopping funnel, optimizing for customer trust and key operational KPIs, while accounting for dynamic changes in the delivery network. Some of the other key projects our team works on include: Graph Neural Network based Policy Abuse detection: GNN model that is robust to sophisticated identity manipulation ( Blog ) Personalization: Uplift model for predicting the effectiveness of different customer service policy Vision-LLM: Gen AI model for automating visual diagnostics and resolution for product refund We are looking for a strong Machine Learning Scientist with deep technical expertise and a proactive, action-oriented mindset. In this role, you will be instrumental in developing and refining the advanced models and systems that power our core mission. You will work in close collaboration with a highly capable, cross-functional team to tackle complex, high-impact challenges and help pioneer innovative solutions.

  • Drive significant business impact by designing, building, and deploying large-scale machine learning models balancing short- and long-term value
  • Conduct exploratory data analysis to uncover data patterns, relationships, and key features for model training.
  • Work cross-functionally with product managers and commercial stakeholders to understand business problems or opportunities, and iteratively develop ML solutions maximizing business ROI
  • Collaborate closely with cross-functional engineering partners
  • Develop key success metrics and build evaluation frameworks to regularly assess model output quality
  • PhD with 0-1+ years of experience or Master's in a STEM field (Engineering, Computer Science, Data Science, Machine Learning, or a related quantitative field) with 2+ years of full-time industry experience in applied research
  • Proven track record of delivering successful machine learning projects from conception to production, demonstrating strong deployment, problem-solving, and maintenance skills.
  • Professional coding expertise in Python, proficiency in SQL, and experience with data visualization tools; skilled in using ML frameworks (TensorFlow, PyTorch) and version control best practices.
  • Strong written and verbal communication skills with an ability to articulate complex technical concepts to technical and non-technical audiences while collaborating within and across teams.
  • Familiarity with GCP (or AWS, Azure), MLOps (feature store, MLflow etc) and orchestration tools (Kubeflow, Airflow)
  • Experience with containerization tools (Docker)
  • Familiarity with causal inference, multi-armed bandits, personalisation
  • Hands-on experience with LLMs
  • Fun team outings like kayaking the Charles and Boda Borg
  • Early adopters of new technology within Wayfair
  • Hackathons to explore new ideas
  • Paid Holidays
  • Paid Time Off (PTO)
  • Full Health Benefits (Medical, Dental, Vision, HSA/FSA)
  • Life Insurance
  • Disability Protection (Short Term & Long Term Disability)
  • Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships)
  • Mental Health Support (Global Mental Health, Global Wayhealthy Recordings)
  • Caregiver Services
  • 401K Matching (Employee Matching Program)
  • Tuition Reimbursement
  • Financial Health Education (Knowledge of Financial Education - KOFE)
  • Tax Advantaged Accounts
  • Family Planning Support
  • Parental Leave
  • Global Surrogacy & Adoption Policy
  • Rewards & Recognition
  • Global Employee Anniversary Awards
  • Paid Volunteer Work
  • Employee Discount
  • U.S. Bluebikes Membership
  • Global Pod Outings
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