Economist

Job description

DESCRIPCIÓN

Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment.

The Amazon Business Supplier Experience team is looking for an Economist who can play a role in multiple areas of the team, including pricing initiatives, leading causal inference and downstream impact studies. This individual will conduct, direct, and coordinate all phases of research projects, demonstrating skill in all stages, including defining key research questions, recommending measures, working with multiple data sources, evaluating methodology and design, executing analysis plans, interpreting and communicating results.

As part of the Amazon Business Supplier Experience organization, the Economist will partner closely with Science, Product, Tech, and Program teams to design innovative solutions to organizational and business problems, communicating highly complex findings to audiences at different levels. The ability to understand and measure the causal effect of Amazon Business features and how to integrate them into downstream optimization 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.

Key Responsibilities:
· Be a thought leader. Conceptualize and lead global research initiatives, understand drivers, impacts, and key influences on cost and pricing dynamics.
· Innovate and drive actions to optimize pricing strategy to improve profitability, growth, and Customer experience.
· Bring deep knowledge of quantitative modeling (ML, optimization, causal modeling) to build econometric models, prototype, and guide the technical approach of production scalable implementations in partnership with technical teams.
· Explain complex technical approaches to a variety of stakeholders, including senior leadership, development teams and cross-functional experts.
· Develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the organization.