John Njau

Key Skills

Software

CrowdSource

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Classification

Freelancer Overview

I am a detail-oriented AI training data specialist with hands-on experience in data labeling, annotation, and content evaluation across text, image, and basic video domains. My background includes supporting digital systems in academic and ICT support roles, where I developed strong skills in data validation, text classification, transcription, and quality assurance. I am adept at handling large volumes of data with high accuracy, ensuring strict compliance with guidelines and maintaining consistency even in repetitive tasks. My technical proficiency spans Microsoft Word, Excel, Google Workspace, and various online platforms, and I have successfully contributed to projects such as designing and testing a secure digital voting system. I am committed to delivering reliable, high-quality training data to power AI solutions.

Labeling Experience

Text Annotation & AI Output Evaluation

CrowdsourceTextClassification

Performed text annotation and AI output evaluation tasks to support training and assessment of language models. Responsibilities included classifying text by intent and relevance, rating AI-generated responses based on accuracy and completeness, validating structured text inputs, and ensuring adherence to detailed annotation guidelines. Handled high-volume datasets requiring consistency, attention to edge cases, and strict quality control. Maintained high accuracy across repetitive tasks and corrected labeling inconsistencies to improve dataset reliability.

Performed text annotation and AI output evaluation tasks to support training and assessment of language models. Responsibilities included classifying text by intent and relevance, rating AI-generated responses based on accuracy and completeness, validating structured text inputs, and ensuring adherence to detailed annotation guidelines. Handled high-volume datasets requiring consistency, attention to edge cases, and strict quality control. Maintained high accuracy across repetitive tasks and corrected labeling inconsistencies to improve dataset reliability.

2025 - 2025

Education

Work History