Machine Learning Scientist

Wayfair - Boston, MA

Full-time - Mid Level

Boston, MA

1,001-5,000 employees

Furniture, Home Furnishings, Electronics, and Appliance Retailers

About the position

The Machine Learning Scientist at Wayfair will design, build, deploy, and refine large-scale machine learning models and algorithmic decision-making systems to solve real-world problems for customers. This role involves collaborating with cross-functional teams to understand business challenges and develop analytical solutions, while also mentoring junior scientists. The position focuses on enhancing the customer experience through advanced machine learning techniques, particularly in areas such as NLP, deep learning, and search algorithms.

Responsibilities

• Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems.
• Work cross-functionally with commercial stakeholders to understand business problems and develop analytical solutions.
• Collaborate with engineering, infrastructure, and ML platform teams to ensure best practices in building and deploying scalable ML services.
• Identify new opportunities and insights from data to improve models and assess the projected ROI of modifications.
• Maintain a customer-centric approach in problem-solving and decision-making.
• Mentor and foster the development of junior ML scientists on the team.

Requirements

• Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field.
• 5-7 years of industry experience in developing machine learning algorithms and deploying them into production at web scale.
• Proficiency in Python or another high-level programming language.
• Familiarity with productionized code bases and PRs; comfort mentoring junior scientists.
• Concrete hands-on expertise deploying machine learning solutions into production.
• Theoretical understanding of statistical models and ML algorithms such as regression, clustering, decision trees, and neural networks.
• Deep domain knowledge in NLP, Deep Learning, or Search & Information Retrieval.
• Strong written and verbal communication skills with the ability to synthesize conclusions for non-experts.
• Intellectual curiosity and enthusiasm for continuous learning.

Nice-to-haves

• Ph.D. in a quantitative field with a track record of relevant publications.
• Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc.).
• Familiarity with cloud ML tooling: Google Cloud Platform, AWS, or Azure.
• Expertise in information retrieval, query/intent understanding, search ranking, and recommender systems.

Benefits

• Opportunities for rapid growth and constant learning.
• Dynamic challenges in a supportive work environment.