Key Responsibilities:• Review and validate human-labeled data to ensure consistency and accuracy for AI training datasets• Identify and resolve discrepancies in data annotations by cross-referencing source materials and guidelines• Collaborate with cross-functional teams to refine annotation guidelines and improve data quality standards• Monitor and report on data labeling performance metrics to track progress and identify trends• Assist in documenting processes and maintaining records of data sources, labeling rules, and quality checks

Required Skills & Qualifications:• Experience with data annotation, labeling, or quality assurance processes is preferred• Familiarity with basic data validation techniques and attention to detail in reviewing datasets• Ability to follow structured guidelines and maintain consistency in data handling tasks• Basic understanding of AI/ML concepts and their dependence on high-quality training data is beneficial• Proficiency in using spreadsheets or data management tools to track and organize information