Danny Sepler
Software Engineer at Propel, Inc
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolDanny Sepler is a software engineer with 11 years of experience building reliable backend and full-stack tooling at startups and enterprises, currently contributing at Propel in New York. He has a track record at Flatiron Health and American Express delivering production-grade services and improving developer experience. An active open-source contributor, Danny has improved NLP tooling in the widely used NLTK project (VADER sentiment testing) and honed Python code quality and shell UX in pycodestyle and xonsh. He leans toward pragmatic engineering: removing legacy Python 2 cruft, tightening tests for deterministic ML behavior, and optimizing interactive tooling performance. Based in NYC, he pairs solid engineering discipline with a taste for small pleasures (tacos > everything), suggesting a practical, people-friendly approach to shipping software.
11 years of coding experience
8 years of employment as a software developer
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at University of Florida
Stackoverflow
61reputation
4kreached
5answers
1question
Github Skills (28)
styles10
pytest10
python10
prompt-toolkit10
testing10
nltk10
guideline10
machine-learning10
sentiment-analysis10
pep10
natural-language-processing10
command-line10
xonsh10
shell10
shortcuts9
Programming languages (8)
Github contributions (5)
nltk/nltk
Aug 2020 - Dec 2021
NLTK Source
Role in this project:
Data Scientist / ML Engineer
Data Scientist / ML EngineerContributions:37 reviews, 28 commits, 27 PRs in 1 year 3 months
Contributions summary:Danny primarily contributed to the `nltk/nltk` repository by modifying and enhancing the sentiment analysis capabilities within the `nltk.sentiment.vader` module. They implemented deterministic behavior in the VADER sentiment analysis model by modifying the test cases. Further contributions added more positive and negative test cases to improve overall model accuracy and performance and also introduced the integration of pytest and its usage.
nlppythonmachine-learningnltknatural-language-processing
PyCQA/pycodestyle
Dec 2021 - Oct 2022
Simple Python style checker in one Python file
Role in this project:Backend Developer
Backend DeveloperContributions:7 reviews, 5 commits, 5 PRs in 10 months
Contributions summary:Danny contributed to the `pycodestyle` project by addressing specific code style issues and improving the functionality of the style checker. Their commits focused on removing Python 2 compatibility code, resolving whitespace issues, and correcting behavior related to tuple handling. The user also worked on refining error reporting, including the removal of outdated warnings, and improving the handling of lambda expressions within the code.
linterpythonstyle-checkercheckerstyle-guide
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