Intern - Economics

Found in: Talent US C2 - 2 weeks ago


Seattle, United States Amazon.com Services LLC - A57 Full time
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and UNIX would be a plus.

These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement.

Roughly 85% of previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at

About the team
The JP Economics team is a central science team working across a variety of topics in the JP Retail business and beyond. We work closely with JP business leaders to drive change at Amazon. We focus on solving long-term, ambiguous and challenging problems, while providing advisory support to help solve short-term business pain points. Key topics include pricing, product selection, delivery speed, profitability, and customer experience. We tackle these issues by building novel economic/econometric models, machine learning systems, and high-impact experiments which we integrate into business, financial, and system-level decision making. Our work is highly collaborative and we regularly partner with JP- EU- and US-based interdisciplinary teams.

We are open to hiring candidates to work out of one of the following locations:

Seattle, WA, USA

BASIC QUALIFICATIONS

PhD student in Economics (enrolled in 3rd year or more and not currently on the job market)

PREFERRED QUALIFICATIONS

Experience with SQL
Familiarity with UNIX
Experience working with large data sets
Knowledge of econometrics
Familiarity with Python
Attention to detail


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