Job Title

As a Senior Manager of Machine Learning Science at Wayfair, you’ll shape the future of how millions of customers are engaged through intelligent, timely, and personalized communication powered by scalable AI systems.Who We AreWayfair 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 Customer Technology (CT) science team builds and owns all the Machine Learning (ML) products that power search, marketing, and recommendation technologies across Wayfair. Our algorithms tackle a 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, to driving marketing experiences customers love at web scale.Within this, the Notifications Science team focuses on building intelligent systems that optimize how and when we engage with customers across channels such as Email, Push, and SMS. These systems balance short-term engagement with long-term customer value, enabling personalized, relevant, and timely communication at scale.About the RoleWe are looking for an experienced machine learning leader to drive the research, development, and execution of ML systems that power Wayfair’s customer engagement and notification platforms. This includes send decisioning, cross-channel optimization, and personalized content selection.In this role, you will be responsible for defining the technical vision and roadmap for Wayfair’s notifications ML stack and leading a team of scientists to deliver high-impact solutions at scale. You will oversee systems that determine which customers to contact, when to contact them, through which channel, and with what content. You will collaborate closely with engineering, analytics, and product partners within CT to align on priorities, execute against roadmaps, and scale impact. This role is a key leadership position within the CT Science organization, with visibility across marketing, product, and platform teams.What You’ll DoLead and grow a team of machine learning scientists, providing mentorship, guidance, and career developmentSet the technical direction and long term roadmap for notification send decisioning, cross-channel optimization, and personalization systemsOversee the development of machine learning systems for notification decisioning under competing objectives, including ranking and personalization componentsDrive the design of multi-objective optimization frameworks balancing short-term engagement, long-term customer value, and customer fatiguePartner closely with product and engineering leaders to define strategy, prioritize initiatives, and deliver scalable ML solutionsEstablish best practices for model development, experimentation, and evaluation, ensuring high standards of quality and rigorEnsure successful end-to-end execution, from problem definition and modeling to experimentation and production deploymentInfluence and align with the broader ML leadership community at Wayfair on best practices, standards, and cross-team initiativesMaintain a strong customer-centric perspective in how problems are framed and solvedWhat You’ll NeedBachelor’s or Master’s degree in Computer Science, Mathematics, Statistics or a related field10+ years of experience building large-scale machine learning systems1-2 years of experience managing or mentoring machine learning scientistsStrong experience in owning ML-driven products or platforms, ideally in ranking, recommendations, ads, or notification systemsProven ability to define and execute on technical roadmaps in cross-functional environmentsStrong theoretical understanding and practical experience applying statistical models and ML algorithms at scaleProficiency in Python and ML frameworks such as TensorFlow or PyTorchStrong communication and stakeholder management skills, with the ability to influence across teamsNice to HavePhD in Computer Science, Mathematics, Statistics or related fieldExperience with marketing technology, customer engagement platforms, or send optimization systemsFamiliarity with multi-objective optimization, causal inference, or experimentation frameworksExperience with Generative AI and its applications in personalization or content generationExperience with cloud platforms (GCP, AWS, Azure) and ML orchestration tools (Airflow, Kubeflow, MLflow) and agentic workflows