Economist I: Data-Driven Growth & Impact

Amazon Inc.; New York (NY); Híbrido; USD 142.000 - 192.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

RSUs

Health insurance

401(k) matching

Descripción de la vacante

Amazon.com Services LLC in New York is seeking a PhD economist to develop econometric models and apply causal inference methods to large data sets. You will work with business stakeholders, scientists, and engineers to solve key problems across AWS, retail, and operations.

The role requires a PhD and a strong research track record; you will communicate complex results to both economists and non-economists and help design automated decision-support systems in a fast-paced environment.

Formación

• PhD in Economics, Quantitative Marketing, Finance, or closely related field.
• Deep knowledge of observational causal inference methods.
• Strong background in statistics and applications to business problems.
• Ability to work in a fast-paced business environment.
• Strong research track record and communication skills.

Responsabilidades

• Develop econometric techniques for large data sets to solve business problems.
• Collaborate with cross-functional teams including economists and engineers.
• Design automated systems and contribute to forecasting and decision making.
• Present findings to stakeholders in clear, non-technical language.

Conocimientos

Observational causal inference

Statistics methods

Fast-paced environment

Research track record

Verbal and written communication

Educación

PhD in Economics or closely related field

Descripción del empleo

Amazon.com Services LLC in New York is seeking a PhD economist to develop econometric models and apply causal inference methods to large data sets. You will work with business stakeholders, scientists, and engineers to solve key problems across AWS, retail, and operations.

The role requires a PhD and a strong research track record; you will communicate complex results to both economists and non-economists and help design automated decision-support systems in a fast-paced environment.