Economist III

• Build econometric models (panel data methods, DiD, RDD, IV) to help measure elasticity, changes in supplier behavior, and customer lifetime value in the presence of endogeneity, simultaneity, and platform dynamics
• Support the development of long-term impact measurement approaches, helping the team move beyond short-term experiment metrics toward quantifying sustained effects on customer retention, partner engagement, and marketplace equilibrium
• Assist in designing and executing causal measurement frameworks for marketplace interventions, including geo experiments, difference-in-differences, synthetic controls, and instrumental variable approaches
• Partner with ML teams to help integrate causal inference into production systems, supporting ranking algorithms, pricing optimization, and recommendation engines with econometrically validated insights
• Translate econometric findings into clear, well-organized analysis and visualizations that support product decisions, and present results to stakeholders with clarity
• Collaborate with data scientists and economists across the organization, contributing to a culture of rigorous causal reasoning and experimental design

• Master's degree in Economics, Applied Economics, Econometrics, Statistics, or a related quantitative field; or Bachelor's degree with equivalent related professional experience
• 0-3 years of relevant professional experience
• Solid foundation in microeconomic theory and applied econometrics, with developing ability to apply appropriate causal inference techniques
• Exposure to applying econometric methods to real-world business problems, in tech, e-commerce, or marketplace environments preferred
• Working knowledge of causal inference tools such as IV, DiD, RDD, synthetic controls, panel data methods, and experimental design
• Proficiency in Python or R with strong SQL skills to work with large-scale, noisy, real-world data, including the ability to query and process data
• Proficient communication skills: ability to explain econometric methodology, identifying assumptions, and business implications to non-technical audiences
• Ability to work both collaboratively and autonomously in a fast-paced business environment

• PhD in Economics, Applied Economics, Econometrics, Statistics, or a related quantitative field
• Coursework, research, or working papers involving applied economics, econometrics, or quantitative methods
• Exposure to marketplace or platform economics: two-sided markets, network effects, dynamic pricing, or general equilibrium modeling
• Exposure to metalearners, doubleML, or causal forests
• Familiarity with modern AI/ML workflows and LLM-assisted analysis tools

The total cash range for this position in Seattle is $137,500.00 to $192,500.00. Employees in this role have the potential to increase their pay up to $220,000.00, 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.