AI Data Labeling & Annotation Specialist / Professor of Accountancy
Labeled and categorized thousands of structured financial and textual datasets for academic research and AI-adjacent studies. Developed rigorous annotation frameworks and detailed rubric guidelines for graduate student research and AI labeling instruction. Conducted quality control and forensic review to identify data anomalies and ensure high data integrity. • Labeled financial documents, disclosures, and written submissions for content, fraud classification, and sentiment analysis • Designed annotation rubrics and instructions applicable to supervised labeling projects • Evaluated and reviewed entity recognition, classification, and relation extraction tasks in academic research • Applied forensic, tax, and compliance domain expertise in data labeling for structured learning datasets