
location_onI 5, First Hill, Seattle, King County, Washington, 98104, United States
Are you passionate about solving some of the most challenging and impactful measurement questions in B2B marketing? AWS Marketing is seeking an Economist to develop the science behind how we measure and optimize brand awareness investment. This is a greenfield opportunity to build a brand measurement capability from the ground up, defining the frameworks, methodologies, and best practices that will shape how AWS thinks about upper-funnel investment.
In this role, you will lead the design and development of a measurement framework for AWS's brand and upper-funnel marketing investments. You will work at the intersection of economics, marketing science, and business strategy to answer critical questions: How much should AWS invest in brand awareness globally, and over what time horizon? What is the impact of brand on customer preferences such as willingness to pay and cost of conversion? How should brand and demand generation investments be combined to maximize overall returns? How do upper-funnel salience metrics connect to revenue and long-term business outcomes?
This is as much a consulting role as it is an analytical one. You will frame investment questions and present findings to senior leadership (VP-level and above), operate independently in a space where established methodology does not yet exist in B2B marketing, and bring external best practices to inform a novel, credible approach tailored for AWS.
Work model: On-site
I 5, First Hill, Seattle, King County, Washington, 98104, United States
Seattle, Washington
Experience in analytics and applied economics, experience in developing and executing an analytic vision to solve business-relevant problems, experience in building statistical models using R, Python, STATA, or a related software, experience in industry, consulting, government or academic research, experience managing and measuring marketing performance in various channels, experience presenting to senior leadership, knowledge of modern machine learning methods and their integration with econometric approaches.
Skills: Econometric Models, Causal Inference, Machine Learning, R, Python, Stata, Multi-Touch Attribution, Incrementality Testing, Brand Measurement.
Education: PhD in Economics required.