Principal Economist, Economic Decision Science

Amazon 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.

Economic Decision Science (EDS) is Amazon’s decision intelligence team for EU Stores. We are a team of economists, engineers, and PMs who apply economic modeling, experimentation, and AI/ML to Amazon’s hardest questions.

Where will Amazon's growth come from in the next year? What about over the next five? Which product lines are poised to quintuple in size? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times? These are among the most important questions at Amazon today.

EDS is hiring a Principal Economist to answer these questions for our European business. The role will work collaboratively with European leaders, Finance teams, and the global Supply Chain Optimization Technology (SCOT) team. You will have an opportunity to own the long‑run outlook for Amazon’s European consumer business and shape strategic decisions at the highest level.

The role will require experience in technical methods at the frontier of economics to develop formal models to understand the past and the present, predict the future, and identify relevant risks and opportunities. For example, we analyze the internal and external drivers of growth and profitability and how these drivers interact with the customer experience in the short, medium and long-term.

We build econometric models of dynamic systems, using our world class data tools, formalizing problems using rigorous science to solve business issues, and further delight customers.

The role is a good fit for candidates with research experience in: macroeconometrics and/or empirical macroeconomics; international macroeconomics; time‑series econometrics; forecasting; financial econometrics and/or empirical finance; and the use of micro and panel data to improve and validate traditional aggregate models.

• PhD in Economics or closely related field.
• Expertise in applied time series.

• Track record of publications that have advanced the state-of-the-art.
• Experience in industry, consulting, government or academic research.
• Fluency in at least one statistical software package such as R, Stata, Matlab, SAS.
• Strong background in econometrics, statistics methodology, machine learning, applications to business problems, and/or big data.
• Experience with programming languages such as Python, Java, C++, experience with SQL and / or working in a Unix / Linux environment is a plus.
• Ability to work in a fast‑paced business environment.
• Effective verbal and written communications skills.