data annotation
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I am an experienced AI Trainer and Evaluator with a strong foundation in Physics, Mathematics, and Chemistry, specializing in data labeling, annotation, and AI training data quality. My background includes hands-on work evaluating and improving AI-generated responses for both STEM and conversational AI applications, using structured rubrics and detailed feedback to enhance model accuracy. I have a proven track record in multi-turn dialogue analysis, hallucination detection, failure mode documentation, and step-by-step reasoning validation, leveraging my technical and academic writing skills. My experience spans LLM testing, prompt understanding, and annotation for educational and conversational AI projects, ensuring high-quality, contextually accurate, and learner-friendly outputs. I am proficient in Python (NumPy, SciPy) and am passionate about driving AI model improvements through meticulous evaluation and data annotation.
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Bachelor of Science, Physics, Mathematics, and Chemistry
Physics & Mathematics Content Writer