Davis Vaughan
Software Engineer at RStudio, Inc.
Charlotte, North Carolina, United States
Summary
🤩
Rockstar🎓
Top School
Top expert inR Data Science and Visualization
Davis Vaughan is a software engineer with a decade of experience focused on improving data analysis tooling in R, currently contributing at RStudio and to flagship tidyverse and r-lib packages. He’s driven deep, performance-minded changes across dplyr, tidyr, tibble, purrr, lubridate and rlang, plus practical financial tooling like tidyquant, blending low-level C/C++ work with high-level API design. His background in mathematical finance and quantitative roles informs a pragmatic approach to reproducible data workflows and feature engineering (recipes) for modeling. Outside core libraries he’s improved developer experience via usethis and pkgdown integrations, showing attention to both user-facing and maintainer ergonomics. Based in Charlotte, NC, he also publishes technical writing and maintains an active GitHub/blog presence that surfaces nuanced solutions to tricky data problems.
10 years of coding experience
5 years of employment as a software developer
Bachelor’s Degree, Mathematics for Business, Senior, Bachelor’s Degree, Mathematics for Business, Senior at University of North Carolina at CharlotteActuarial ExamsHigh Point Christian Academy
Stackoverflow
2,875reputation
84kreached
87answers
2questions
r
top-5%
Github Skills (51)
algorithm10
algorithms10
c-language10
script-setup10
github10
template-metaprogramming10
multidimensional-arrays10
package-development10
data-manipulation10
r10
machine-learning10
c1110
tidyverse10
setup-wizard10
data-structure10
Programming languages (17)
Github contributions (5)
tidyverse/tidyr
Mar 2019 - Jan 2023
Tidy Messy Data
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 98 reviews, 347 commits in 3 years 10 months
Contributions summary:Davis primarily contributed to the tidyr R package by implementing and improving core functionality. They addressed issues related to R 3.1 support, enhanced the performance of `pivot_wider()`, and updated the package to align with changes in dplyr 1.0.0. Additionally, they introduced performance improvements to `unchop()` and rewrote the rectangling functions, demonstrating a strong understanding of data manipulation and optimization techniques within the R ecosystem.
tibbledataframestidymodelstidydplyr
tidyverse/dplyr
Feb 2020 - Jan 2023
dplyr: A grammar of data manipulation
Role in this project:Back-end Developer
Back-end DeveloperContributions:346 reviews, 331 commits, 466 PRs in 2 years 11 months
Contributions summary:Davis focused on optimizing the `dplyr` package's data manipulation capabilities. Their contributions included improving the efficiency of existing functions like `join_rows()` and `n_distinct()`. They also worked on enhancing the core functionality of the package, such as fixing sequential updating within data masks, implementing new features like `.by` support, and refactoring existing ones like `group_split()` and `recode()`. They also implemented improvements to data frame construction and attribute handling.
manipulationpolarsdata-analysisduckdbgrammar
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