Moses Aaron Crasto

Designed and implemented a machine learning model for automatic product categorization, leveraging both image and text data from the Etsy platform. Built and optimized custom Convolutional Neural Networks (CNNs) and integrated EfficientNet to enhance multi-modal analysis, improving model performance on diverse product types. Designed data pipelines for preprocessing, augmentation, and feature extraction, ensuring robustness on noisy datasets, enabling accurate detection of product categories and color attributes. Delivered a solution with high predictive accuracy, enhancing search functionality, product discoverability, and overall user experience on the Etsy marketplace.

Designed and implemented a machine learning model for automatic product categorization, leveraging both image and text data from the Etsy platform. Built and optimized custom Convolutional Neural Networks (CNNs) and integrated EfficientNet to enhance multi-modal analysis, improving model performance on diverse product types. Designed data pipelines for preprocessing, augmentation, and feature extraction, ensuring robustness on noisy datasets, enabling accurate detection of product categories and color attributes. Delivered a solution with high predictive accuracy, enhancing search functionality, product discoverability, and overall user experience on the Etsy marketplace.

Developed a Time Management System, implementing features for precise task tracking and analysis, which improved team productivity and project management. Worked alongside cross-functional teams in an Agile setting, actively participating in planning meetings to maintain alignment and achieve timely project milestones. Engaged in code reviews and quality assurance processes, applying best practices to enhance code quality and system performance. Acquired hands-on experience with version control systems, continuous integration/continuous deployment (CI/CD) pipelines, and enterprise-level software development methodologies.