Elizabeth T
Senior ML Data Engineer
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolElizabeth T is a Senior ML Data Engineer with 12 years of experience blending data engineering, MLOps, and applied research, currently building production ML data pipelines at SimpliSafe. She holds a Ph.D. in Biology and transitioned from postdoctoral work in microbiology and genetics into industry roles that span startups and enterprise teams, bringing strong experimental rigor to data-centric systems. Elizabeth has led data science and MLOps efforts at companies including iRobot and Healthie, and contributed to high-impact open-source work on the Hugging Face datasets hub by adding low-resource Filipino NLP datasets for hate speech, fake news, and entailment tasks. A certified FIDE School chess instructor and long-time freeCodeCamp top contributor, she combines teaching, community engagement, and a knack for making complex ML datasets usable in production.
12 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy Biology General, Doctor of Philosophy Biology General at Kobe University
Github Skills (9)
machine-learning10
nlp10
python10
natural-language-processing10
data-science10
datasets10
pandas8
pytorch6
tensorflow6
Programming languages (4)
Github contributions (5)
huggingface/datasets
Dec 2020 - Dec 2020
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Role in this project:
Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:5 commits, 6 PRs, 4 comments in 3 days
Contributions summary:Elizabeth primarily contributed to adding and integrating new datasets focused on Filipino language processing, specifically for tasks like hate speech detection, fake news classification, and sentence entailment. They created dataset scripts, including data loading, feature engineering, and metadata, which is critical for the usage of the datasets in downstream ML tasks. The user's contributions demonstrate a focus on expanding the repository's capabilities to support low-resource language research and the application of NLP to social media data.
ml-modelstensorflownatural-language-processingmanipulationdata-science
anaerobeth/python-coding-exercises
May 2017 - Nov 2019
Contributions:61 pushes, 2 branches in 2 years 6 months
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