Individual contributor role focused on causal inference and marketplace measurement work impacting billions of dollars in transaction value on a large travel platform.
Locations (2)
Seattle, Washington, United States
Austin, Texas, United States
Compensation
The total cash range for this position in Seattle is $119,000.00 to $166,500.00. Employees in this role have the potential to increase their pay up to $190,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. The total cash range for this position in Austin is $119,000.00 to $166,500.00. Employees in this role have the potential to increase their pay up to $190,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Responsibilities
Build econometric models (panel data methods, DiD, RDD, IV) to help measure elasticity, changes in supplier behavior, and customer lifetime value
Support the development of long-term impact measurement approaches
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
Translate econometric findings into clear, well-organized analysis and visualizations that support product decisions
Support causal inference and marketplace measurement work for Expedia Group's Economics and Experimentation Science team.
Locations (2)
Seattle, Washington, United States
Austin, Texas, United States
Compensation
The total cash range for this position in Seattle is $119,000.00 to $166,500.00. The total cash range for this position in Austin is $119,000.00 to $166,500.00.
Responsibilities
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
Requirements
Master's degree in Economics, Applied Economics, Econometrics, Statistics, or a related quantitative field
Bachelor's degree with equivalent related professional experience
Nice to have: PhD in Economics, Applied Economics, Econometrics, Statistics
