I am a Principal Economist at Amazon, where I work on large-scale empirical modeling and decision-intelligence systems at the intersection of macroeconomics, econometrics, and operations. My work focuses on time-series forecasting, causal inference, and Bayesian methods applied to complex, high-dimensional economic and operational environments, with direct applications to supply chain planning, growth analysis, and experimentation.

Prior to joining Amazon, I spent over a decade in academic positions. I served as an Assistant Professor at the University of Illinois at Urbana-Champaign  from 2016-2023,  held faculty appointments at Goethe University Frankfurt from 2010-2016, and was a Visiting Assistant Professor in the Department of Economics the University of Pennsylvania during 2015-2016). 

I received my Ph.D. from the Department of Economics at Humboldt University in Berlin.

My Research interests include empirical macroeconomics, Bayesian econometrics, monetary policy,  and macro-finance, with an emphasis on combining rigorous econometric methods with real-world decision making. My research has been recognized with the Quantitative Economics Best Paper Prize awarded by the Econometric Society (2021-202 cycle).

Curriculum Vitae: CV 

Private Email: pooyanamirahmadi [at] googlemail [dot] com