Staff Economist - Customer Technology

About The Team The Customer Technology Science (CTS) organization builds the intelligence behind how customers discover products and how suppliers reach customers across Wayfair. Our teams span Search, Recommendations, Advertising, Marketing, Experimentation, and Causal Inference, solving some of the most consequential marketplace optimization problems at Wayfair scale. We are looking for a Staff Economist to shape the scientific foundations of Wayfair's advertising and marketplace decision systems. You will work at the intersection of economics, causal inference, machine learning, experimentation, and market design, developing systems that jointly optimize customer experience, supplier outcomes, and Wayfair's long-term platform value. This is a highly influential staff IC role. You will define scientific direction across areas such as auction design, bidding and budget optimization, ads and organic ranking, incrementality measurement, personalization, and automated advertiser decisioning. You will partner closely with senior leaders across Science, Product, Engineering, and Commercial teams to translate economic principles into production systems operating at massive scale. What You Will Do Shape marketplace optimization strategy: Define economic and scientific frameworks for jointly optimizing customer experience, supplier value, marketplace health, and Wayfair's long-term economics. Advance decision and market design: Develop principled approaches to ranking, allocation, pricing, incentives, and auction mechanisms across customer and supplier-facing systems. Optimize product discovery: Help shape how Search, Recommendations, and Ads balance relevance, personalization, conversion, monetization, and long-term customer value through multi-objective optimization and economic arbitration. Build next-generation measurement systems: Advance experimentation and causal inference in environments where interference, selection effects, network effects, heterogeneous treatment effects, and long-term behavioral responses make conventional A/B testing insufficient. Model customer and marketplace behavior: Apply structural and reduced-form economic methods to understand behavioral responses, simulate counterfactual policies, and anticipate equilibrium effects of major product, algorithmic, or marketplace changes. Develop intelligent decision systems: Shape personalization, targeting, ranking, bidding, budget allocation, and other automated decisions using econometrics, machine learning, optimization, bandits, and reinforcement learning. Explore AI-native decision making: Define how foundation models and agentic systems can improve customer experiences, supplier decision support, personalization, experimentation, and automated optimization. Set the scientific standard: Provide technical leadership across economists, scientists, and engineers through rigorous problem formulation, methodological review, mentorship, and development of reusable scientific frameworks. Influence senior leadership: Translate complex market dynamics, causal evidence, and algorithmic trade-offs into clear recommendations for VP- and C-level decision makers. Advance the field: Contribute to Wayfair's scientific community through publications, external research engagement, and participation in conferences such as KDD, NeurIPS, RecSys, WSDM, EC, and related communities. What You’ll Need PhD in Economics, Econometrics, Quantitative Marketing, Statistics, Computer Science, or a related quantitative STEM field with 8+ years of industry experience, OR Master’s Degree with 10+ years of industry experience. 5+ years of experience as a Technical Lead or Science Lead specifically within Advertising Science, Retail Media Networks, Marketing Tech, or Multi-Sided Marketplace Optimization. Demonstrated success defining scientific strategy and translating sophisticated economic or statistical methods into large-scale production systems and business decisions. Strong understanding of modern machine learning and emerging AI paradigms, including generative recommendation, foundation models, large-scale sequential and long-context user modeling, multimodal learning, ranking and personalization, bandits, reinforcement learning, and multi-objective optimization. Strong quantitative modeling and computational skills, with fluency in modern AI-assisted and agentic coding workflows to rapidly prototype, evaluate, and productionize scientific ideas. Proven track record of operating as a senior technical leader across organizational boundaries, setting direction and raising the scientific bar without relying on formal reporting authority. Demonstrated ability to partner seamlessly across Product, Engineering, and Business leadership to shape, own, and execute multi-year scientific and technical roadmaps. Preferred Qualifications Experience applying economics and machine learning to large-scale consumer or marketplace systems, particularly in e-commerce, search and recommendations, advertising, marketing, or pricing. Expertise in multi-objective optimization, market design, dynamic pricing, auction design, contextual bandits, reinforcement learning, or causal machine learning. Experience with generative recommendation, sequential user modeling, foundation models, multimodal systems, or agentic AI applied to customer or marketplace decision systems. Ability to prototype and operationalize economic and statistical models in collaboration with engineering teams, using modern data, ML, and agentic development tooling. Track record of publications, patents, or engagement with research communities such as ACM EC, KDD, NeurIPS, ICML, RecSys, SIGIR, WSDM, or Marketing Science. 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 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. Your personal data is processed in accordance with our Candidate Privacy Notice ( If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at View email address on click.appcast.io. #J-18808-Ljbffr Wayfair