Global Talent Management (GTM) is centrally responsible for creating and evolving Amazon’s human capital and talent programs and processes.
People Science Team within GTM is a growing start-up team with direct impact on Amazonians across all of our businesses and locations around the world. We play a crucial role in ensuring top notch data products and insights facilitate our growth and development of talent in intelligent and curious ways. We regularly use data to pitch ideas and drive conversations with Amazon’s Senior Vice President of HR and other executives about how to improve existing talent programs to solve organizational problems focused on (but not limited to) talent differentiation, talent movement, employee-role matching, product integration, promotion practices, organization design and succession planning, and diversity and inclusion, or invent new ones that address the evolving needs of our diverse employee base.
We are looking for a self-driven Economist to help shape analytics and research roadmap and enable data-driven innovation that fuel our rapidly scaling talent management mission. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at GTM will be expected to develop new techniques to process large data sets, apply a causal lens to the framework, address ambiguous business problems, and contribute to design of automated systems around the company.
You will partner closely with product and program owners, as well as scientists and engineers from other disciplines (e.g. data science, software engineers, data engineering) with a clear path to business impact. You develop innovative and even frighteningly bold plans and ideas to discover new ways to advance our goals. You will be expected to be a thought leader as we chart new courses with our rapidly growing employee populations, and lead the way in experimenting new ideas that have not yet been explored.
· Participate in scoping and planning of GTM’s Science roadmap
· Uncover drivers, impacts, and key influences on talent outcomes
· Build new econometric models to improve existing talent products or those that make the case for new products
· Bring a causal lens to questions in human resources employing either experiments or non-experimental approaches
· Develop predictive and optimization models for key applications
· Navigate a variety of data sources, such as enterprise data, customize surveys, focus groups, and/or external data sources
· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
· Work in expert cross-functional teams delivering on demanding projects
· PhD in Economics, Quantitative Marketing, Finance, or closely related field.
· 0-1 years experience in industry, consulting, government or academic research
· Applicants with considerably more experience, including mid-career, are also strongly encouraged.
· Some prior experience with Python and/or Machine Learning approaches is preferred.
· Strong background in statistics methodology, applications to business problems, and/or big data.
· Ability to work in a fast-paced business environment.
· Strong research track record.
· Effective verbal and written communications skills.
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us