Senior Machine Learning Scientist

Location: Boston, MA Who We Are Wayfair's Machine Learning teams are the driving force behind our business success, consistently enhancing the customer experience and building customer loyalty. Our Machine Learning Science (MLS) Catalog team is dedicated to harnessing the power of machine learning to enable supplier-facing decision-making through the use of customer data. We focus on critical tasks such as extracting product tags, conducting catalog comparisons, and identifying high-potential SKUs. We partner closely with Merchandising, Catalog Operations, and Engineering to build scalable algorithmic systems responsible for sustaining a well-defined Wayfair catalog. We are looking for an experienced Machine Learning Scientist to join the Data Science Catalog team, with emphasis on developing scalable algorithms and platforms to power Wayfair’s engine to match identical and highly similar products to improve customer experience and discoverability of Wayfair’s large product offering. You will work together with other machine learning scientists, as well as multiple merchandising and engineering teams to solve one of our most impactful and intellectually challenging data science problems at Wayfair. What You'll Do - Develop product matching models using Wayfair’s imagery & text data sources to deduplicate, curate and organize Wayfair’s catalog - Integrate model outputs into a variety of end use cases with partner business and engineering teams to drive value for Wayfair - Work with partner engineering teams (Catalog DS Eng.) to build real-time models & services for widespread consumption across Wayfair - Develop the next generation of matching operations & decision support systems to automate operations in adding new products to Wayfair’s catalog - Communicate results and influence decision making with senior stakeholders to drive improvements in end-to-end processes What You'll Need - 3+ years of experience in a quantitative or technical work environment with an advanced degree (PhD) in a quantitative field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.) or 4+ years of experience with a Masters in a quantitative field - Machine Learning using a wide range of techniques (such as supervised/weakly supervised learning, computer vision, deep learning, etc.) - Proficient at one or more programming languages, e.g. Python, Java, C++, etc. - Prior experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc. - Prior experience formulating problems that can be solved with ML, evaluation with appropriate metrics and driving value for business use cases. - Experience with cloud compute (i.e. GCP, AWS), schedulers (i.e. Airflow), and containerization (Docker) are nice to have - Ability to effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions - A bias towards solving problems and an intuitive sense for how the work aligns closely with business objectives - Ability to thrive in a dynamic environment where there can be varying levels of ambiguity Assistance for Individuals with Disabilities Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accommodations for Applicants form. Need Assistance? For more information about applying for a career at Wayfair, visit our FAQ page here. About Wayfair Inc. Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking. No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic. We are interested in retaining your data for a period of 12 months to consider you for suitable positions within Wayfair. Your personal data is processed in accordance with our Candidate Privacy Notice (which can found here: https://www.wayfair.com/careers/privacy). If you have any questions regarding our processing of your personal data, please contact us at [email protected]. If you would rather not have us retain your data please contact us anytime at [email protected].