Ivan A.

I work on the data quality tasks that help AI systems produce more reliable results: reviewing outputs, labeling information, checking annotations against instructions, identifying errors, and validating structured data. My experience combines computer science, data handling, and detailed quality checks. I have worked with structured datasets, spreadsheets, explicit labeling rules, approved-value lists, text normalization, and post-processing checks to catch inconsistencies and errors. I have also reviewed AI-generated outputs and research summaries for factual accuracy, relevance, completeness, and whether claims are supported by their sources. I pay attention to the details that are easy to overlook: inconsistent labels, missing information, formatting errors, incorrect classifications, and cases where an instruction has not been followed precisely. Tasks I can support: - AI data annotation and labeling - Text classification and categorization - AI response evaluation and quality review - Data validation, cleaning, and consistency checks - Error detection and annotation verification - Structured data review using Excel, Google Sheets, and Python where appropriate - Following detailed annotation guidelines and documenting ambiguous cases I have a Computer Science degree and professional experience working with technical systems and structured operational data. I am comfortable learning project-specific tools and following established quality standards. My priority is accurate, consistent work that follows the client's instructions.