Nathan Parsons
Senior Software Engineer at Grid Status
Holland, Michigan, United States
Summary
🤩
Rockstar🎓
Top SchoolNathan Parsons is a Senior Software Engineer based in Holland, Michigan with two decades of multidisciplinary engineering experience and nine years focused on software. He builds full-stack Python systems (Django, FastAPI) and data tooling, and has been a primary maintainer on notable open-source projects at Alteryx such as Featuretools and EvalML where he contributed feature engineering, pipeline improvements, and scalability fixes. His background uniquely combines machine learning and data science with hands-on mechanical engineering expertise—FEA, vibration testing, additive manufacturing and powertrain labs—enabling pragmatic solutions for both software and physical-product problems. At GridStatus.io he continues to apply this cross-domain fluency to production systems, CI/CD, and developer tooling. Colleagues rely on him for pragmatic architecture, robust testing (pytest), and easing the path from prototypes to maintainable, production-ready pipelines.
9 years of coding experience
25 years of employment as a software developer
Master's degree, Agricultural Engineering, Master's degree, Agricultural Engineering at Purdue University
Stackoverflow
386reputation
7kreached
13answers
0questions
Github Skills (21)
python10
data-science10
scikit10
pandas10
machine-learning10
feature-engineering10
compose10
dask10
automl10
scikit-learn10
testing9
numpy9
pipelining9
user-manual9
pipe9
Programming languages (6)
Github contributions (5)
alteryx/open_source_demos
May 2020 - Jan 2023
A collection of demos showcasing automated feature engineering and machine learning in diverse use cases
Role in this project:
Data Scientist
Data ScientistContributions:13 reviews, 49 commits, 35 PRs in 2 years 8 months
Contributions summary:Nathan contributed a tutorial demonstrating the use of Featuretools and Dask for feature engineering on a large dataset from Instacart. They implemented data loading, preprocessing, and the creation of an EntitySet to facilitate feature generation. Their work focused on creating a feature matrix suitable for training a machine learning model, highlighting the scalability benefits of using Dask. The commits also show updates to the tutorial, including version notes and dependency management.
casesdiversepythonuse-casesdata-science
alteryx/featuretools
Apr 2019 - Jan 2023
An open source python library for automated feature engineering
Role in this project:Back-end Developer
Back-end DeveloperContributions:19 releases, 722 reviews, 228 commits in 3 years 9 months
Contributions summary:Nathan's contributions primarily involved updating and modifying existing transform primitives in the featuretools library, specifically within the standard primitives module. Their work focused on enhancing these primitives by adding support for new data types like Boolean and addressing functionality issues such as ensuring ordinal comparisons. They also implemented new primitives such as RateOfChange and refined serialization and deserialization processes to improve efficiency and compatibility with Woodwork. These changes improve Featuretools capabilities for automated feature engineering.
python-librarypythondata-scienceautomated-machine-learningmachine-learning
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.