Nita Uche

Detail oriented and quality-focused QC Annotator with experience reviewing, validating, and improving AI-generated content and data labeling outputs. Skilled in quality control processes, annotation accuracy verification, rubric-based evaluations, and identifying inconsistencies across datasets. Strong ability to perform high-volume review tasks while maintaining accuracy, consistency, and compliance with project guidelines.

Experienced in providing actionable feedback, escalating quality issues, and supporting continuous improvement initiatives in AI training workflows.

AI Reviewer and Trainer - Freelance / Remote Projects

(2026-01)

• Reviewed and evaluated AI-generated responses based on predefined rubrics and quality standards.
• Performed fact-checking and verification of AI outputs to ensure accuracy and reliability.
• Labeled and categorized data to support AI model training and improvement.
• Ranked AI responses according to relevance, clarity, helpfulness, and correctness.
• Completed high-volume repetitive tasks while maintaining strong attention to detail and consistency.
• Supported workflow improvements by providing feedback on annotation processes and review guidelines.

AI Data Annotator - DATALENS AFRICA - Independent Contractor

(2024-02 - 2025-12)

• Annotated text, image, and conversational datasets to improve AI model performance and training accuracy.
• Identified inconsistencies, bias, and inaccuracies in AI-generated outputs and flagged them for correction.
• Evaluated chatbot and language model responses for fluency, coherence, tone, and contextual relevance.
• Compared multiple AI-generated answers and selected the most accurate and user-friendly responses.
• Applied detailed annotation guidelines and labeling taxonomies to maintain consistency across datasets.

DATA ANNOTATION & AI TRAINING - DATALENS AFRICA