On independent remote AI evaluation projects, I scored more than 10,000 model responses across finance, reasoning, coding and general knowledge. I ranked LLM responses for RLHF, identified hallucinations and reasoning errors, and created reusable checklists that cut turnaround time by about 25%.
At Annotasks and Atlas Capture, I annotated and validated more than 250,000 records for machine learning datasets, maintaining 99% annotation accuracy. I also used Python and Excel to analyze evaluation trends, and hold certifications in Google Data Analytics, IBM Data Science and Microsoft Azure AI Fundamentals.

