Wayfair Machine Learning Science powers automation and decision support across all Wayfair business units. Our algorithms tackle a varied and 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 and diverse assortment of home goods. Wayfair Professional is Wayfairs B2B org; our mission is to be the destination for all things furniture, fixtures and equipment (FF&E) for every business. We serve professional customers in many industries, including Interior Design, Commercial Office, Contractor, Property Management, Accommodations, Foodservice, and Education, with cross-functional teams focused on improving the customer experience in each target vertical / industry.
Wayfair Professional Machine Learning (ML) builds and maintains ML products supporting Wayfair Professionals growing portfolio of business initiatives. We use first- and third-party data to identify Professional customers and their industries, characterize spending patterns, make optimal recommendations to sales agents, and match customers to the best customer experience both on-site and with their account managers. With applications in marketing, sales, storefront, and pricing, the Wayfair Professional ML team has a uniquely broad impact.
As a Machine Learning Scientist within the Wayfair Professional ML, you will develop and deploy ML products that power algorithmic decision-making across the business. Youll process petabytes of first- and third-party data, deploy both real time models triggered by customer actions (sub-second SLA) and batch models (hundreds of millions of predictions daily) into production, measure impact using Wayfairs A/B and MAB testing platforms. Ultimately, youll leverage a wealth of data and your ML expertise to maximize ROI on billions of annual customer interactions.
What You'll Do
- Build machine learning models to drive algorithm decision making across Marketing, Sales, Storefront, Operations & Pricing domains for Wayfair Professional
- Build highly scalable distributed data processing platforms that evaluate the long-term incremental value of our millions of offerings and of actions that the business can take
- Collaborate with other data scientists to build high quality ML models that can robustly scale up to large volumes in production
- Partner closely with various business & engineering teams to drive the integration of our model outputs & algorithmic decision-making systems into existing production systems
- Youll be a builder of tools, software, and microservices that enhance or streamline various steps or challenges within the data science workflow & our tech stack
- Extend existing ML libraries and frameworks for scalable model training & deployment
- Own the full data science life cycle: scoping to prototyping, testing, deploying, measuring value and iterating
- Identify and innovate new opportunities to drive business results through data science
What You'll Need
- 2+ years of experience in a quantitative or technical work environment, and advanced degree (MS, PhD) in a quantitative field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.)
- Thorough command of general data science and machine learning techniques
- Machine Learning experience (supervised/unsupervised learning, reinforcement learning, deep learning, etc.). A strong understanding of fundamental concepts related to performance metrics, feature selection, model calibration, hyperparameter tuning, etc. is essential
- Proficient at Python. Knowledge of other programming languages like R, Java, etc. is a plus; experience with Spark is a plus.
- Comfortable with SQL and ability to wrangle data from various sources. Experience using cloud based tools is a plus.
- Good understanding of experimental techniques (A/B tests, MAB tests, pre-post tests) and related statistical analysis methods
- Commercial experience in production-environment-driven ML design (e.g. having deployed at least one ML solution to scale, etc.) is a strong plus
- Ability to work on cross-functional projects and manage multiple stakeholder groups with competing priorities and different degrees of technical fluency
- Communication skills that can influence across organizations and levels
- Ability to thrive in a dynamic environment where there can be degrees of ambiguity
- Ability to focus on business value / ROI
About Wayfair Inc.
Wayfair is one of the worlds 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, were 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 youre looking for rapid growth, constant learning, and dynamic challenges, then youll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. Were 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. Thats why were 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, or genetic information.
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].