Description
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. This particular position is for a economist in the Forecasting, Macroeconomics, and Finance (FMF) track to help us develop and deploy forecasting models and carry out analyses that support critical processes at AWS
Knowledge of time-series 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 econ-internship@amazon.com.
A day in the life
AWS Central Economics and Science takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don’t encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed and excited. It makes for bigger impact, faster skill accrual and thus career advancement.
About the team
FACE is the Forecasting team in AWS Central Economics and Science. We provide AWS leadership, Finance, and Planning teams with science-based forecasts and analysis to optimize financial and operational planning at various levels of granularity. Our models implement frontier science at the intersection of economics, statistics and machine learning. The output of our models and analyses supports critical processes at AWS such as Operational Planning and Quarterly Guidance. We are a close-knit, highly collaborative, and interdisciplinary team of scientists who are experts in their respective fields.
Basic Qualifications
PhD student in Economics (enrolled in 3rd year or more and not currently on the job market)
Preferred Qualifications
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $55.91/hr in our lowest geographic market up to $96.63/hr in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. 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, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.