مُصنّف البيانات

Role Purpose

Prepare high-quality, consistently labeled data that supports the development, evaluation, and improvement of machine learning and AI systems. Apply project guidelines to text, images, audio, video, or other data types, flag unclear or sensitive cases, and work with reviewers and project leads to resolve annotation issues and maintain reliable datasets.

Key Responsibilities



• Review project instructions and annotation guidelines before starting each task, and ask for clarification when instructions are unclear or conflicting.

• Label, classify, transcribe, categorize, or otherwise annotate assigned data using the project’s approved tools and standards.

• Apply labels consistently across text, images, audio, video, or other data formats, according to the needs of each project.

• Check completed annotations for accuracy, completeness, consistency, and correct use of the defined labels.

• Flag ambiguous, incomplete, low-quality, or potentially sensitive data for review rather than making unsupported assumptions.

• Incorporate reviewer feedback and update annotations when required.

• Meet project timelines while following documented quality and data-handling procedures.

• Maintain the confidentiality and security of project data, and use it only for authorized work.

• Document recurring questions or guideline gaps and share them with the project lead to support process improvements.

Qualifications and Experience

• High school diploma or equivalent; further education is an advantage.

• Strong attention to detail and the ability to follow written instructions consistently.

• Good reading and comprehension skills in the languages required by the project.

• Basic computer skills and confidence using web-based tools, spreadsheets, and annotation platforms.

• Ability to manage repetitive tasks while maintaining focus and accuracy.

• Clear written communication and willingness to receive and apply feedback.

• Previous experience in data annotation, content review, transcription, or quality checking is an advantage.

• Ability to handle confidential information responsibly and follow data protection procedures.