image annotation, text categorization
I have hands-on experience in AI training and data labeling tasks, with a focus on image annotation and text categorization. In image annotation work, I have performed bounding box labeling, object detection tagging, and semantic segmentation for visual datasets — ensuring accurate identification of objects, spatial relationships, and scene context required for computer vision model training. In text categorization, I have worked on classifying content by intent, sentiment, and topic relevance — tasks involving ranking model-generated responses, evaluating coherence and factual accuracy, and labeling data for NLP pipelines. My experience also includes prompt evaluation, where I assess AI outputs for tone, logical consistency, and alignment with user intent. My background in Business Analytics gives me a strong foundation in structured thinking, pattern recognition, and quality judgment — skills directly applicable to reviewing and rating AI-generated content at scale. I am comfortable working with annotation guidelines, maintaining high inter-rater reliability, and flagging edge cases that require human judgment. Domains I can contribute to: Marketing & consumer behavior data, business communication, e-commerce content, survey data classification, and general English-language AI evaluation tasks.