AI Training Data Labeling & Content Annotation Specialist
Worked on structuring and annotating text-based datasets to improve content clarity, categorization, and usability for AI-driven systems. Tasks included labeling social media posts, technical content, and educational materials based on sentiment, intent, topic classification, and audience relevance. Ensured consistency in tagging by following strict annotation guidelines and performing regular quality checks. Handled both structured and unstructured data across multiple formats, refining outputs to meet high accuracy standards. Contributed to improving dataset reliability by identifying ambiguous entries, maintaining labeling consistency, and optimizing content for machine learning applications. Project scope included hundreds of data samples weekly, with a strong focus on precision, scalability, and adherence to quality assurance protocols. Additional Information (optional) Strong background in copywriting and content strategy, with proven ability to understand context, tone, and intent—key advantages in high-quality data annotation. Experienced in working with fast-paced, detail-oriented workflows and adapting quickly to new labeling frameworks and tools.