Job Description
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment.
Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond.
Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets - applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of cross-functional team embedded within a business unit. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
About the team
QuBIT Science (Midas team) is revolutionizing data-driven decision-making across Amazon's operations. We specialize in delivering swift, scientifically rigorous solutions that often fall outside the immediate scope of larger central science organizations.
We are currently seeking an economist to join our team. The ideal candidate will have expertise in causal inference, causal discovery, and prediction modeling. The successful applicant will be passionate about executing end-to-end science projects, applying advanced scientific methods to operational data to solve complex business challenges. This role offers a unique opportunity to directly impact Amazon's operational efficiency through applied economic analysis.
BASIC QUALIFICATIONS - PhD in economics or equivalent
PREFERRED QUALIFICATIONS - 2+ years of industry, consulting, government, or academic research experience
- Knowledge of at least one statistical software package such as R, Stata, Matlab, SAS
- Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks)
- Experience with handling of large datasets
- Experience in prediction and forecasting in a research or industrial environment
- Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets
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 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 $136,000/year in our lowest geographic market up to $212,800/year 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 workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Job Tags
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