Data Annotation & Quality Reviewer (Independent)
Organized output information into clear summaries, stepwise explanations, and structured documentation for diverse educational and operational use cases. Focused on clarity, factual alignment, and improving model-generated content quality through detail-oriented review. Applied summarization and annotation to technical documentation, exam-style explanations, and workflow logic designs. • Created structured summaries from complex technical content and AI outputs. • Annotated key facts, errors, and logic gaps for continuous AI improvement. • Leveraged annotation to enhance automated documentation and task handover. • Supported content quality control for educational materials and user-facing guides.