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Description

Global Talent Management (GTM) owns a suite of products which help drive career development for hundreds of thousands of Amazonians globally. GTM Science utilizes a wide array of data sources to conduct analytics and create predictive models that fuel recommendations, actions, and insights within the software systems that support Amazonians throughout their employee journeys. The team itself is composed of scientists and engineers with diverse backgrounds and expertise, coming together to create innovative solutions to the problems faced by the one of the world’s largest and fastest growing workforces.

This role will support the advancement of key workforce planning products owned by the team. You’ll lead a small team focused on forecasting inputs and outputs of the workforce planning process, helping leaders better understand the trajectory of Amazon’s workforce. You will do this by building econometric models, using world class data systems, and directly applying economic theory to solving business problems in a fast moving environment. You’ll work with other Scientists at Amazon developing new techniques, processing large data sets, addressing quantitative problems, and contributing to the design of automated systems around the company.

If you’re interested in seeing your research and models get used regularly by thousands of Amazonians, and working in a large inter-disciplinary science team that helps to inform talent management decisions, this role is for you.

Basic Qualifications

- PhD in business economics, engineering, analytics, mathematics, statistics, information technology or equivalent

- Experience communicating technical concepts to a non-technical audience

- Must have the ability to communicate relevant scientific insights from data to senior business leaders

Preferred Qualifications

- 6+ years of post PhD experience experience

- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives

- Experience in Python, Stata, and/or R

- Experience with experimental design in complex business settings, measuring lagged effects

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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 $187,500/year in our lowest geographic market up to $324,100/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 https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.