Advanced Financial Logic & Python Code Evaluation for LLM Optimization
Led a specialized data labeling project focused on fine-tuning Large Language Models (LLMs) for high-accuracy financial programming and quantitative analysis. My work involved reviewing AI-generated Python code specifically designed for financial modeling, including interest rate swap valuations and risk management scripts. I performed detailed RLHF tasks by ranking model responses based on logical soundness, syntax accuracy, and adherence to financial regulatory standards like IFRS 9. Additionally, I authored 'Gold Standard' responses for complex prompts involving SQL database optimization and ETL pipeline debugging within a fintech context.