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.
Key job responsibilities
Collaborate with business and science colleagues to understand the business problem and collect relevant data. Provide statistically rigorous analysis of data that contributes to business decision-making. Effectively communicate your results to colleagues and business leaders.
A day in the life
Meet with colleagues to discuss how the business currently works. Discuss ways in which the customer experience could be improved, and what data you'd need to test your hypotheses. Meet with data and business intelligence engineers to build an efficient data pipeline using SQL, spark and other big data tools. Propose and execute a plan to analyze your data, working closely with your econ colleagues. Use Amazon's development tools, coding your estimators in Python or R. Draft your findings for an internal knowledge sharing session. Iterate to improve your work and communicate your final results in a business document.
About the team
We are a team of four economists that works within the Delivery Experience org. Our goal is to improve the delivery experience for our customers while reducing costs. This mission puts us in a unique position to influence both the front end customer experience and the supply chain that ultimately places constraints on that experience. This means we often work with and influence teams outside of our own organization. As a result, we have the privilege of working with a diverse group of experts, including those in supply chain, operations, capacity management, and user experience. - PhD student in Economics (enrolled in 3rd year or more and not currently on the job market)
- Familiarity with R or Python- Experience working with large data sets
- Experience in structural/IO economics
- Knowledge of applied econometrics
- Attention to detail
- Experience with SQL
- Excellent communication skills to technical and non-technical audiences
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