TRMS is seeking for an experienced economist in applied micro and empirical IO with demonstrated industry, policy, or academic experience. You will apply economic theory to build econometric models, and prototype and put into production scalable implementations in partnership with technical teams, using Amazon's world class data systems. You will be expected to be a thought leader as we chart new courses with our policy abuse prevention technologies. Successful candidates will have a deep knowledge of quantitative modelling in at least one area (ML, optimization, causal modeling and experimentation), the ability to build and refine models that can be implemented in production, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long-term problems.
As part of the TRMS organization, you'll partner closely with Science, Product, Tech, and Program teams to design innovative solutions to organizational and business problems, communicating highly complex findings to multiple audiences. The ability to understand and measure causal policy effects and integrate and optimize them into downstream abuse prevention systems is a highly valuable asset. You may come from any one of a variety of econometric backgrounds, but you must be comfortable with multiple modeling techniques, be able to acquire new techniques with practice, and be willing to show flexibility in finding the right technique to match the research problem. We expect you to work closely with software engineers to put algorithms into practice.
* Conceptualize and lead global research initiatives * Guide the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects * Conduct, direct, and coordinate all phases of research projects, demonstrating skill in all stages of the analysis process, including defining key research questions, recommending measures, working with multiple data sources, evaluating methodology and design, executing analysis plans, interpreting and communicating results * Functionally decompose complex problems into simple, straight-forward solutions
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