Prema Roman
Director Of Engineering at Georgetown University
Virginia, United States
Summary
🤩
Rockstar🎓
Top SchoolPrema Roman is a Director of Engineering based in Virginia with 11 years of experience building data-intensive, distributed systems and machine learning platforms. She has progressed from analytics and data engineering roles into leadership positions across financial services and consulting, most recently leading engineering at Rotational after heading ML and principal data engineering efforts at Navy Federal. Hands-on background includes senior software engineering and data engineering at Tick Data and Excella, and she teaches practical ML and engineering topics as an adjunct lecturer at Georgetown University. An active contributor to open-source ML tooling, she implemented visualizers and model-diagnostic features for the popular yellowbrick project, blending data science intuition with production engineering. Known for turning complex analytical requirements into maintainable pipelines, she brings both technical depth and cross-functional leadership to scale ML systems in regulated environments.
11 years of coding experience
19 years of employment as a software developer
BS, Management Information Systems, Marketing, BS, Management Information Systems, Marketing at George Mason University
Github Skills (13)
scikit10
pandas10
machine-learning10
visualization10
visualizations10
python10
matplotlib10
scikit-learn10
feature-engineering9
regression8
classification8
visualizer7
anaconda7
Programming languages (5)
Github contributions (5)
DistrictDataLabs/yellowbrick
Mar 2017 - Aug 2022
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Role in this project:
Data Scientist
Data ScientistContributions:2 reviews, 25 commits, 65 PRs in 5 years 6 months
Contributions summary:Prema contributed extensively to the `yellowbrick` repository, primarily focusing on creating and integrating visualizers for machine learning tasks. Their work involved implementing visualizations for feature analysis, model selection, and evaluation. Key contributions include the development of a Feature Visualizer, JointPlotVisualizer, and CVScores visualizer, along with various tests and documentation updates for these and other visualizers.
pythonvisual-analysisvisualizermodel-selectionmachine-learning
pdamodaran/yellowbrick
Jun 2018 - Aug 2022
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Contributions:1 PR, 97 pushes, 52 branches in 4 years 2 months
pythonvisual-analysismodel-selectionmachine-learningdiagnostic
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.