Sr. Economist, Topline Forecasting

Amazon • Bellevue, WA • 8h ago

Description

Where will Amazon's growth come from in the next year? What about over the next five? What are the drivers and factors of such growth? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times? These are among the most important questions at Amazon today. The Forecasting team in the Supply Chain Optimization Technologies (SCOT) organization is dedicated to answering these questions using quantitative and statistical methods. We build accurate predictive models and deploy automated software solutions to provide forecasting insights to business leaders at the most senior levels throughout the company.

Economists in the Forecasting, Macroeconomics & Finance field document, interpret and forecast Amazon business dynamics. This position is well suited for economists adept at combining times-series statistical methods with strong economic analysis and intuition. It could be a good fit for candidates with research experience in: macroeconometrics and/or empirical macroeconomics; international macroeconomics; time-series econometrics; forecasting; financial econometrics and/or empirical finance; and the use of micro and panel data to improve and validate traditional aggregate models.

Economists at Amazon are expected to work directly with our senior management and scientists from other fields on key business problems faced across Amazon. The Forecasting, Macroeconomics & Finance field utilizes methods at the frontier of economics to develop formal models to understand the past and the present, predict the future, and identify relevant risks and opportunities. For example, we analyze the internal and external drivers of growth and profitability and how these drivers interact with the customer experience in the short, medium and long-term. We build econometric models of dynamic systems, using our world class data tools, formalizing problems using rigorous science to solve business issues and further delight customers.

Basic Qualifications

PhD in economics or equivalent

Experience in econometrics (e.g., program evaluation, forecasting, time series, panel data, or high dimensional problems), economic theory, and quantitative methods

Preferred Qualifications

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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.

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