Research Scientist - Economist

Microsoft•Redmond, WA

17h•$102,100 - $202,200•Onsite

About The Position

This position is in the Office of the Chief Economist at Microsoft’s Seattle-area headquarters. We are not like other industry jobs: we value both excellence in academic research and internal impact. Our group sits within Monetization and Business Planning. This is an ideal job for economists who value an opportunity to do academic research that makes a large impact in the real world.

Requirements

Master's Degree in relevant field AND 1+ year(s) related economic research experience OR Bachelor's Degree in relevant field AND 2+ years related economic research experience OR equivalent experience.

Nice To Haves

Doctorate in relevant field OR Master's Degree in relevant field AND 3+ years related research experience OR Bachelor's Degree in relevant field AND 5+ years related research experience OR equivalent experience.
Proficiency in R or Python, including common tools for data manipulation (e.g., dplyr, pandas, polars), graphing, and causal inference
Knowledge of standard econometric methods in "small data" (e.g., difference in differences, matching, synthetic control) and "big data" setting (e.g., double machine learning)
Experience publishing academic papers as a lead author or essential contributor.
Experience participating in a top conference in relevant research domain.
Experience with Spark or other tools for processing big data
Experience developing custom empirical models and methods for pricing and/or market design

Responsibilities

Research economists work closely with Corporate Vice President, Chief Economist, Michael Schwarz, and the team of economists and data scientists on high-impact projects in a supportive research environment.
Topic areas include advertising effectiveness, media economics, market design, electricity, cloud marketplaces, search auctions, optimal pricing contracts, retail product competition, scalable demand estimation, structural demand estimation, machine learning for both prediction and causal inference, optimal capacity investment, economics of subscriptions, and other applied theory.
Successful candidates should drive their own agenda as well as work with the broader team.
Candidates with the following backgrounds have historically done well in this environment: empirical IO, applied micro, econometrics, and quantitative marketing.