Josiah Parry
Senior Product Engineer at R Consortium
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJosiah Parry is a Senior Product Engineer at Esri with a decade of experience blending spatial data science and software engineering, particularly in Rust and R. He builds performant geospatial tools and contributes to open-source data-cleaning workflows, notably extending janitor's clean_names for sf and tbl_graph objects with robust unit tests. Based in Seattle, he bridges product engineering with community stewardship as Esri’s representative and Vice Chair on the R Consortium Infrastructure Steering Committee. His background spans government-facing customer success, teaching urban informatics, and applied methodology roles—giving him a rare mix of user-centered product thinking and rigorous statistical practice. Colleagues rely on him for reliable, production-ready spatial tooling and pragmatic automation that scales beyond research prototypes. An unassuming polymath, he often pairs low-level systems work in Rust with high-level reproducible analyses in R.
10 years of coding experience
1 year of employment as a software developer
Diploma, Photography, Diploma, Photography at Marin School of the ArtsBachelor of Arts (B.A.), Cum Laude, Sociology, Bachelor of Arts (B.A.), Cum Laude, Sociology at Plymouth State UniversityMaster of Science - MS, Urban Informatics, Master of Science - MS, Urban Informatics at Northeastern University
English
Github Skills (7)
sfx10
sfc10
tidyverse10
r10
data-analysis8
data-science7
testing7
Programming languages (25)
Github contributions (5)
sfirke/janitor
Oct 2018 - Dec 2018
simple tools for data cleaning in R
Role in this project:
Data Scientist
Data ScientistContributions:12 commits, 2 PRs, 10 comments in 1 month
Contributions summary:Josiah primarily focused on enhancing the `clean_names` function within the `janitor` R package, specifically tailoring it for use with Spatial Data objects (`sf`). Their work included creating methods for `sf` and `tbl_graph` objects. The user added and improved unit tests to ensure correct behavior and maintain data cleaning consistency, including handling edge cases and diverse name formats. The commits demonstrate a focus on extending the functionality and robustness of data cleaning tools within the project's data science focus.
spsstabulationsdata-analysistidyverser-package
JosiahParry/sfdep
Jan 2022 - Jan 2023
A tidy interface for spatial dependence
Contributions:2 releases, 16 reviews, 147 commits in 1 year
spatial-analysisdependencespatialr-spatialrstats
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