Data Analytics & AI Tutor (Annotation Focus) — Annotation review, feedback, and dataset curation (Jan 2024–Present)
Produced and reviewed text classification labels for machine learning exercises, ensuring adherence to rubric guidelines and annotation standards. Checked student outputs for labeling consistency, accuracy, and rule compliance while mirroring real-world QA workflows in annotation pipelines. Curated model-ready training datasets by applying cleaning and formatting best practices to support downstream ML training. • Labeled and validated text categorization and pattern identification tasks using structured exercises. • Provided detailed written feedback to flag errors and enforce consistent labeling across cohorts. • Resolved annotation disagreements by referencing and updating guidelines to improve inter-student agreement. • Monitored quality and consistency trends across 20+ students per cohort.