AI Data Workflow & Annotation Quality (TD Bank)
Expanded expertise in AI data workflows, annotation quality, and structured labeling principles to support AI training. Applied knowledge of annotation quality control in an enterprise setting focusing on bias reduction, accuracy, and consistency. Worked on aligning process data and categorizing requests through rule-based classification for improved workflow automation. • Applied structured labeling for project data categorization. • Used rule-based classification to identify high-risk process items. • Implemented quality control concepts for annotation accuracy. • Drove operational improvements with AI-aligned labeling methods.