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Senior Economist, PXT Central Science

Amazon Science

Arnhem
Full-time
10+ years experience
On-site

Key Skills

Economics
Causal Inference
Applied Econometrics
Statistical Modeling
Python
R
STATA
Machine Learning
Statistical Programming
Large-Scale Data Analysis
Research Design
Impact Measurement
Team Leadership
Scientific Communication
Research Agenda Development
AI Tools

Job Description

Description The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for a Senior Economist who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations, and analytics teams to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. They will lead teams of researchers to produce robust, objective research results and insights which can be communicated to a broad audience inside and outside of Amazon. The ideal candidate has a PhD in Economics and deep expertise in causal inference and applied econometrics. Experience with large-scale data, proficiency in statistical programming (Python), and familiarity with machine learning methods are a plus. To be successful in this role, you should be comfortable operating with ambiguity, able to independently scope and prioritize research agendas, skilled at influencing decisions through rigorous analysis, and comfortable with using AI tools. Basic Qualifications PhD in economics or equivalent Preferred Qualifications Experience in analytics and applied economics Experience in developing and executing an analytic vision to solve business-relevant problems Experience in building statistical models using R, Python, STATA, or a related software Experience in industry, consulting, government or academic research 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.

Core Responsibilities

Structure complex business problems into scientific questions, develop models and algorithms using large-scale data, and design pilots to measure impact. Lead research teams in producing robust, objective insights and help scale successful prototypes into improved policies and programs.

Requirements

A PhD in economics or equivalent is required, with deep expertise in causal inference and applied econometrics. The role also calls for comfort with ambiguity, independent research prioritization, and the ability to influence decisions through rigorous analysis; experience with large-scale data, statistical programming, machine learning, and AI tools is advantageous.

About Amazon Science

Industry: Research Services

Company size: 10,001+ employees

Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Follow us on LinkedIn and visit our website to get a deep dive on innovation at Amazon, and explore the many ways you can engage with our scientific community. #AmazonScience

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