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Senior Economist - Advertising Technology

$184.5k

Traveltechessentialist

Expedia Group brands power global travel for everyone, everywhere. We design cutting‑edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. Why Join Us? To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time‑off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us. Senior Applied Economist - Advertising Technology Introduction to the Team Expedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high‑quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction. We are seeking an Economist to join our high‑performing Advertising Technology team to drive rigorous, data‑driven decisions across auction design, ad relevance, incrementality measurement, and marketplace optimization . This role sits at the intersection of economic theory, applied statistics, econometric modeling, experimentation, and large‑scale ad systems , influencing how ads are ranked, priced, and evaluated in production. You will work closely with Data Science, Machine Learning, Engineering, Product, and Operations to translate statistically and economically sound analysis into scalable marketplace improvements. In this role, you will: Analyze and improve ad auction mechanisms (pricing, bidding, pacing) and model advertiser behavior to balance revenue, ROI, relevance, and user experience Define and evaluate ad relevance signals using statistical and econometric methods to ensure incentive‑aligned metrics Design and analyze incrementality and causal experiments (geo tests, holdouts, switchbacks) to measure true lift and avoid cannibalization Build and validate econometric and causal models to understand marketplace dynamics, pricing, and long‑term health Conduct advanced data analysis to inform product strategy, policy decisions, and marketplace optimization Collaborate cross‑functionally with product, engineering, and ML teams to drive experimentation and data‑driven decisions at scale Communicate clear, actionable insights to technical and non‑technical stakeholders Minimum Qualifications Master’s or PhD in Economics, Applied Economics, Econometrics, Statistics, Operations Research , or a related quantitative field Solid foundation in microeconomic theory and game theory , with the ability to model strategic behavior Strong background in applied statistics and econometric modeling Proficiency in Python or R with strong SQL skills to work with large‑scale, noisy, real‑world data Hands‑on experience with statistical modeling (linear, GLM, panel data), causal inference techniques, hypothesis testing, and uncertainty quantification Strong analytical thinking and a passion for empirical, data‑driven research to explore and answer complex questions Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products Excellent written and verbal communication skills , with the ability to clearly convey complex quantitative analysis, methodologies, and insights to diverse stakeholders Preferred Qualifications Experience in advertising, auctions, ranking, or marketplace platforms Experience with incrementality measurement in production environments Track record of delivering actionable insights from experimental design, causal inference, or large‑scale data analysis Demonstrated leadership in designing, implementing, and scaling AI/ML‑enabled solutions that improve business outcomes Expertise in integrating generative AI tools to enhance economic modeling, scenario analysis, or forecasting applications Background in e‑commerce, travel, or large‑scale marketplaces The total cash range for this position in Seattle is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future. Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits. Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E‑Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee’s I‑9 to confirm work authorization. #J-18808-Ljbffr Traveltechessentialist

Vacancy posted 1 day ago
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