- PhD student in Economics (enrolled in 3rd year or more and not currently on the job market)
- Knowledge of econometrics and machine learning, in particular causal methods for microdata
- Familiarity with Python/R
- Attention to detail
The AWS HR Economics and Applied Science Team is hiring Interns in Economics. We come up with innovative ways to use econometrics, ML, and economic theory to improve the experience of AWS employee and to help HR/recruiters put the right people in the right place at the right time to staff all of AWS.
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 and machine learning, as well as basic familiarity with Python and/or R is necessary, and experience with SQL, UNIX, and Spark would be a plus.
You will develop causal inference models to assess all decisions surrounding talent: drivers of promotion, attrition, transfers, and hires and you will identify and work with external and internal talent data-sets and develop ways to combine the two to answer important talent research questions.
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, engineers, 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 50% of research assistants from previous cohorts have converted to full time data science or economics employment at Amazon. If you are interested, please send your CV to our mailing list at email@example.com.
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
- Experience with SQL
- Familiarity with UNIX
- Familiarity with Spark
- Experience working with large data sets