AI Financial Data Annotation Specialist (RLHF Evaluator)
Designed and applied an AI evaluation framework for financial text (equities, macro, and options). Tasks included labeling model outputs using RLHF-style evaluation—scoring accuracy, reasoning quality, and market validity, identifying errors, and rewriting responses to improve correctness. Worked across hundreds of examples with consistent structured outputs. Quality was maintained through standardized scoring criteria, strict focus on factual accuracy, and review of edge cases to ensure reliability and consistency.