*Prepared and annotated diverse datasets (text, images, tabular records) to improve machine learning accuracy
*Prepared and annotated diverse datasets (text, images, tabular records) to improve machine learning accuracy. *Designed structured labeling guidelines and applied quality control checks to ensure consistency and reliability. *Collaborated with technical teams to integrate labeled datasets into training pipelines for healthcare and government automation projects. *Evaluated AI system outputs against labeled benchmarks, identifying edge cases and reducing bias. *Contributed to iterative model refinement, enhancing scalability and real‑world performance. *Documented workflows and results to support transparency and reproducibility in AI projects.
Not specified