AI Data Labeling & Document Intelligence Specialist (HR & Business Data)
As part of my experience supporting AI training workflows, I worked on labeling and structuring large volumes of unstructured and semi-structured HR documents. This involved annotating employee records, policy documents, and performance reports to create high-quality training data for downstream analysis and model learning. I tagged key data points such as employee information, compensation components, KPIs, and compliance-related details, ensuring each label was applied consistently in line with defined annotation guidelines. I also classified documents into relevant categories (e.g., employee records, policies, performance reports) to support document classification tasks. In addition, I standardized extracted data into structured formats and performed quality assurance checks to validate accuracy, completeness, and consistency of annotations. This process contributed to improving data reliability for AI models focused on document understanding and business data analysis. This experience strengthened my ability to apply data labeling techniques such as classification, entity tagging, and information extraction with a high level of precision and attention to detail