Jv Eclarin
Data Scientist
Houston, Texas, United States
Summary
👤
Senior🎓
Top SchoolJv Eclarin is a data scientist and software developer with eight years of technical experience and four years in professional roles, currently applying ML and data engineering skills at Adaptalytics in Houston. He blends practical production work—automating ETL, building a Streamlit app that processed hundreds of PDFs in hours, and automating ticket conversion—with research experience in materials characterization from Rice University. An active contributor to testing infrastructure for high-profile open-source projects like PyTorch Lightning, he ensures reliability as APIs evolve by updating tests across callbacks, checkpointing, and trainer utilities. As a founder of a non-profit research group, he has led multidisciplinary teams on projects ranging from 3D printing and patent strategy to ML for music and market prediction, showing both technical breadth and organizational grit. Known on GitHub as "snakes and letters," he brings a chemical engineering background to data-driven problem solving, favoring pragmatic automation that saves weeks of manual work.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Chemical Engineering, Bachelor's degree, Chemical Engineering at University of Houston
Github Skills (10)
pytorch10
pytest10
python10
testing10
ai9
machine-learning9
artificial-intelligence9
deep-learning9
deeplearning-ai8
data-science8
Programming languages (4)
Github contributions (5)
Lightning-AI/pytorch-lightning
Jan 2022 - Mar 2022
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:38 reviews, 15 commits, 16 PRs in 2 months
Contributions summary:Jv primarily contributed to the testing infrastructure of the `pytorch-lightning` repository, focusing on updating tests to align with changes in the API, specifically regarding the use of the `devices` parameter. Their commits modified numerous test files across various components like callbacks, checkpointing, trainer utilities, and core functionalities. These changes ensure the continued reliability of the library with evolving parameters, maintaining code quality through rigorous testing.
pythonheadachespytorch-modelsdata-sciencehandling
mathemusician/AudioTranscription
Oct 2021 - Dec 2021
Contributions:104 commits, 50 pushes, 1 branch in 1 month
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