Grant Mcdermott
Principal Economist at Amazon
Eugene, Oregon, United States
Summary
🤩
Rockstar🎓
Top SchoolGrant Mcdermott is a Principal Economist at Amazon with 11 years of experience blending environmental and natural resource economics, applied econometrics, and data science to solve big-data problems. He moved between academia and industry—from an assistant professorship at the University of Oregon and a UCSB postdoc to private-sector roles—bringing rigorous empirical methods to production-scale analytic problems. Grant is a hands-on contributor to open-source R tools used by applied researchers, notably improving modelsummary and broom to better handle clustered standard errors and tidy marginal effect outputs. His work spans machine learning, cloud computation, and Bayesian approaches, and he has a track record of translating messy, large datasets into actionable insights. Based in Eugene, Oregon, he pairs a PhD from NHH with practical experience in finance, development fundraising, and field-facing roles, reflecting an uncommon mix of technical depth and real-world stakeholder engagement.
11 years of coding experience
6 years of employment as a software developer
Business Science, Business and Economics, Business Science, Business and Economics at University of Cape TownMaster of Science - MS, International Management, A, Master of Science - MS, International Management, A at CEMS - The Global Alliance in Management EducationDoctor of Philosophy - PhD, Economics, Doctor of Philosophy - PhD, Economics at Norwegian School of Economics (NHH)
English, Afrikaans, Norwegian
Github Skills (9)
tidy10
statistics10
statistical-models10
statistic10
modeling10
tidyr10
r10
testing10
package-development9
Programming languages (21)
Github contributions (5)
tidymodels/broom
Aug 2019 - Jun 2022
Convert statistical analysis objects from R into tidy format
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:67 commits, 10 PRs, 38 comments in 2 years 10 months
Contributions summary:Grant contributed significantly to the `broom` package by adding tidiers for the `mfx` and `lmtest` packages, specifically for `logitmfx` and `probitmfx`. These tidiers facilitate the conversion of statistical analysis objects into a tidy format. The user also added examples, fixed regular expressions and function names, and added tests, thus improving functionality, usability, and quality assurance for the `broom` package.
r-packagestatisticshypothesis-testingregression-modelstidymodels
vincentarelbundock/modelsummary
Aug 2020 - Aug 2021
Beautiful and customizable model summaries in R.
Role in this project:Data Scientist
Data ScientistContributions:14 commits, 8 PRs, 66 comments in 1 year
Contributions summary:Grant primarily contributed to the `modelsummary` R package by adding and modifying functions related to model summary output for various statistical models. Their work included adapting the package to support specific features of the `fixest` and `did` packages, which involved modifying existing functions to handle different model types and output standard errors and cluster variables. Additionally, the user improved the display of clustered standard errors within the summary output, and added tests to validate these changes and ensure the correct rendering of interaction terms.
r-packagestatisticshypothesis-testingbookdownregression-models
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