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Economist – Data-Driven Forecasting & Causal Inference

Amazon, New York, NY, United States


Job ID: 3207039 | Amazon Web Services, Inc. - A97 MULTIPLE POSITIONS AVAILABLE

Employer: AMAZON WEB SERVICES, INC. Offered Position: Economist III Job Location: Jersey City, New Jersey Job Number: AMZ9674161

Position Responsibilities:

Work with the chief economist and senior management on key business problems faced in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, or operations. Apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising, and other areas. Build econometric models using data systems. Apply economic theory to solve business problems. Develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems. Apply tools from applied micro-econometrics (e.g. experimental design, difference-in-difference, regression discontinuity, and IV) and forecasting (essential time series models). Leverage big data tools for data extraction. Write up and present analysis for distribution to various levels of management at Amazon. Gain experience in academic research. Use program evaluation, forecasting, time series, panel data, and high dimensional problems. Use R and Stata.

Position Requirements:

Ph.D. or foreign equivalent degree in Economics, Finance, or a related field and three years of research or work experience in the job offered or a related occupation. Must have at least one year of research or work experience in the following skill(s): (1) working with Causal inference techniques (Difference-in-Differences, Matching, Double Machine Learning, Instrumental Variables, and Regression Discontinuity Designs); (2) statistical analysis tools (Python, R or Stata); (3) Data querying languages (SQL).

Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.

40 hours / week, 8:00am-5:00pm, Salary Range $175,100/year to $236,900/year.

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, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000 Basic Qualifications

Position Requirements:

Ph.D. or foreign equivalent degree in Economics, Finance, or a related field and three years of research or work experience in the job offered or a related occupation. Must have at least one year of research or work experience in the following skill(s): (1) working with Causal inference techniques (Difference-in-Differences, Matching, Double Machine Learning, Instrumental Variables, and Regression Discontinuity Designs); (2) statistical analysis tools (Python, R or Stata); (3) Data querying languages (SQL).#0000 Preferred Qualifications

Please see job description and the position requirements above.

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. Posted:

January 20, 2026 (Updated about 6 hours ago) Posted:

January 20, 2026 (Updated about 6 hours ago) Posted:

March 25, 2026 (Updated about 17 hours ago) Posted:

March 2, 2026 (Updated about 19 hours ago) Posted:

March 24, 2026 (Updated about 20 hours ago) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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