Michiel Paris

About Michiel Paris

I am an applied economist at Amazon, where I use causal inference methods to estimate the effect of cost drivers on key metrics and machine learning to create driver-based forecasted financials. I have a PhD in Economics from Cornell University and over six years of experience in applying economic theory and data analysis to solve complex and impactful business problems. I also have over three years of experience managing small teams of junior economists: setting tasks, iterating on written and coding output, and providing mentorship. My mission is to generate insights that inform and improve decision-making, strategy, and innovation at Amazon and beyond. I collaborate with cross-functional teams of economists, data scientists, engineers, and business leaders to tackle challenging and relevant problems. I am passionate about finding novel approaches and solutions that leverage data, technology, and economic theory.

Experience

1. Economist Ii

   Amazon

   May 2022 — Present · Seattle, WA, US

   Used machine learning to create forecasted financials and allow customers to create scenarios based on alternative driver time series- Led project to find causal estimates of the effect of cost drivers on key financials.

Education

• Cornell University

  Doctor of Philosophy - PhD, Economics

  2012 — 2018

• London School of Economics and Political Science

  BSc, Economics

  2003 — 2006

• UWC Atlantic College

  High School

  2001 — 2003

• University of Oxford

  MPhil, Economics

  2006 — 2008