
Worked on the OTAnalytics repository to enhance code maintainability, data reliability, and analytics user experience. Focused on backend development and application logic using Python and Pandas, refactoring image counting by centralizing logic and standardizing naming conventions for clarity. Improved data export robustness by filtering count-dataframe columns to handle missing data gracefully, increasing reliability. Introduced a new plotting architecture with Matplotlib, enabling automatic GUI plot updates and decoupling plot saving from visualization logic. Emphasized code standardization, documentation, and modular organization throughout the process, resulting in a more maintainable and responsive analytics pipeline with improved data visualization and export capabilities.
May 2025 OTAnalytics: Focus on code health, data reliability, and analytics UX. Delivered key features that strengthen maintainability, data reliability, and visualization capabilities; improved business value through robust data export, clearer code organization, and responsive visualizations across the pipeline.
May 2025 OTAnalytics: Focus on code health, data reliability, and analytics UX. Delivered key features that strengthen maintainability, data reliability, and visualization capabilities; improved business value through robust data export, clearer code organization, and responsive visualizations across the pipeline.

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