mozilla/gecko-dev
Jul 2025 – Jul 2025
1 Month active
Languages Used
JavaScript
Technical Skills
Data AnalysisFront End DevelopmentMachine LearningNew Tab PagePersonalization
Mitchell Plyler
PROFILE
Mitchell Plyler
Developed a data-driven personalization feature for the New Tab shortcuts in the mozilla/gecko-dev repository, focusing on improving shortcut relevance and user engagement. Leveraged JavaScript and data analysis techniques to implement a Thompson sampling-based ranking system, dynamically adjusting shortcut suggestions based on user interaction data such as clicks, impressions, and frecency. The work involved refactoring the existing ranking pipeline to support experimentation and facilitate reviewer feedback, ensuring robust integration with the broader codebase. This approach laid the foundation for measurable business value by enabling more relevant recommendations, while demonstrating proficiency in front end development, machine learning, and cross-functional collaboration.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
508
Activity Months1
Your Network
901 peopleSame Organization
@mozilla.com401
Shared Repositories
500
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 (2025-07) performance summary for mozilla/gecko-dev: Delivered data-driven personalization for New Tab shortcuts by implementing Thompson sampling-based ranking. Refactored the shortcut ranking pipeline to incorporate interaction data (clicks, impressions) and frecency, enabling dynamic, relevance-driven recommendations. Linked changes to Bug 1972392 and completed associated code changes to support experimentation and reviewer feedback. Impact: improved potential relevance and engagement of New Tab shortcuts, with groundwork for measurable business value. Demonstrated strong data-driven engineering, refactoring, and cross-functional collaboration with reviewers (home-newtab-reviewers, firefox-ai-ml-reviewers).
1 Commits • 1 Features
Jul 1, 2025July 2025 (2025-07) performance summary for mozilla/gecko-dev: Delivered data-driven personalization for New Tab shortcuts by implementing Thompson sampling-based ranking. Refactored the shortcut ranking pipeline to incorporate interaction data (clicks, impressions) and frecency, enabling dynamic, relevance-driven recommendations. Linked changes to Bug 1972392 and completed associated code changes to support experimentation and reviewer feedback. Impact: improved potential relevance and engagement of New Tab shortcuts, with groundwork for measurable business value. Demonstrated strong data-driven engineering, refactoring, and cross-functional collaboration with reviewers (home-newtab-reviewers, firefox-ai-ml-reviewers).
July 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaScript
Technical Skills
Data AnalysisFront End DevelopmentMachine LearningNew Tab PagePersonalization
Repositories Contributed To
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