Rebecca Bilbro
Founding Engineer - Enterprise Division at Fractional AI
Raleigh, North Carolina, United States
Summary
🤩
Rockstar🎓
Top SchoolRebecca Bilbro is a technology executive and founding engineer with 11 years of experience building and scaling AI-driven products at the intersection of data science, software engineering, and leadership. She has founded and led startups and teams—most recently architecting LLMs, fine-tuning, prompt engineering, and RAG systems at Rotational Labs and now delivering bespoke enterprise automations at Fractional AI. A former adjunct data science faculty at Georgetown and core contributor to Yellowbrick, she blends rigorous pedagogy and clear communication with pragmatic engineering to make complex ML workflows accessible. Her background spans government analytics, NLP-driven productization, and open-source visualization tooling, evidencing both research chops and production impact. Collected across a PhD in technical writing and degrees in math and English, she brings an uncommon humanities-informed perspective to AI design and team mentorship.
11 years of coding experience
17 years of employment as a software developer
William G. EnloeData Analytics Certification Data Science, Data Analytics Certification Data Science at Georgetown UniversityDoctor of Philosophy (PhD) Professional Technical Business and Scientific Writing, Doctor of Philosophy (PhD) Professional Technical Business and Scientific Writing at University of Illinois Urbana-ChampaignBA Mathematics and English, BA Mathematics and English at Skidmore College
English, French
Stackoverflow
477reputation
19kreached
8answers
0questions
Github Skills (33)
data-visualizations10
data-pipelines10
python10
evaluation10
classification10
scikit10
machine-learning10
data-visualisation10
eval10
natural-language-processing10
pipe10
pipeline10
scikit-learn10
data-visualization10
nlp10
Programming languages (10)
Github contributions (5)
DistrictDataLabs/yellowbrick
May 2016 - Aug 2022
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Role in this project:
Data Scientist
Data ScientistContributions:5 releases, 20 reviews, 129 commits in 6 years 4 months
Contributions summary:Rebecca contributed to the development and documentation of model visualization methods within the yellowbrick library. They added docstrings to various methods and classes for classification reports, ROC curves, and prediction error plots, enhancing the usability and understandability of the tools. Their work included refactoring the score method for a visualizer and adding quick methods to facilitate easier usage.
pythonvisual-analysisvisualizermodel-selectionmachine-learning
foxbook/atap
Mar 2018 - Nov 2020
Code for Applied Text Analysis with Python
Role in this project:Data Scientist
Data ScientistContributions:11 commits, 15 pushes, 61 comments in 2 years 8 months
Contributions summary:Rebecca made several updates to code related to text analysis and machine learning within the repository. Their contributions involved modifications to the corpus reader, potentially for pre-processing text data, and implementations of various machine learning models. They further integrated and utilized scikit-learn for tasks like entity extraction and classification, demonstrating proficiency in building and evaluating machine learning pipelines. The revisions also extended to model training and evaluation, along with the visualization and presentation of results.
nlpdata-analysispythontopic-modelingnatural-language-processing
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