Intern - Economics, CloudTune Forecasting
Description
Amazon's CloudTune Forecasting team is hiring Interns in Economics. 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 Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark 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, data scientists and MBAʼs. 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 interns from previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
About The Team
CloudTune Forecasting team develops large-scale scale models to inform team-level budget allocations and procurement/allocation of compute capacity for Amazon businesses during new product launches, high velocity events and non-peak periods. Scientist in the team will be contributing to a managed service that uses historical data and business signals to deliver time series forecasting for specialized use cases. The service combines a variety of distinct forecasting models to produce highly accurate forecasts.
Responsibilities
Requirements
Basic Qualifications
- PhD in Economics or closely related field
- Familiarity with Python/R/Stata/Matlab, or other similar programming languages
To be considered for an economist internship in 2022, applicants should be enrolled in at least the third year of their PhD program and not currently on the job market.Preferred Qualifications
- Experience with SQL
- Familiarity with UNIX
- Familiarity with Sawtooth
- Familiarity with Apache Spark
- Experience working with large data sets
