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I have experience working with AI training data and data labeling projects focused on improving machine learning model performance, accuracy, and content quality. My work has included text annotation, sentiment analysis, content moderation, categorization, transcription review, and prompt-response evaluation for generative AI systems. I am skilled at following detailed annotation guidelines, maintaining high accuracy standards, and identifying inconsistencies in datasets to ensure reliable outputs for AI model training and evaluation. What sets me apart is my strong attention to detail, analytical thinking, and ability to work efficiently under tight deadlines while maintaining quality. I am comfortable using various data labeling and quality assurance tools, collaborating with remote teams, and adapting quickly to new project requirements. Additionally, my communication skills, problem solving ability, and commitment to accuracy make me well-suited for AI training data projects that require precision, consistency, and critical evaluation.
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Bachelor of Arts, History and International Studies
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