Gabriel Aduyemi

Analytical and detail-driven Content Analyst with a strong background in data annotation, linguistic evaluation, and quality assurance across text, image, video, and audio datasets. Skilled in reviewing, labeling, and refining large volumes of English-language content under tight deadlines, maintaining balance between speed and precision. Experienced in AI/LLM evaluation, communication-based content review, and documentation for evolving project workflows.

Data Annotator at Scale AI (2025-06 – 2025-12)

• Executed content labeling and analytical evaluation for AI datasets with high adherence to project guidelines.
• Managed large task volumes with consistent accuracy and speed under time constraints.
• Conducted linguistic and contextual quality reviews of English text, audio, and image data.
• Applied structured documentation methods to report guideline ambiguities and improve data integrity.
• Collaborated with research and QA teams to refine machine learning outputs and ensure guideline compliance.

Content Analyst & Reviewer at Valum AI (2023-08 – 2024-12)

• Reviewed and evaluated English-language text, video, and image content for clarity, accuracy, and compliance with policy standards.
• Performed content moderation and quality checks across high-volume data environments.
• Balanced speed and quality using time-sensitive workflows and system-generated timers.
• Contributed to guideline documentation and identified edge cases for process refinement.
• Maintained professionalism and composure in fast-paced, deadline-driven tasks.

Medical Transcriptionist at Fiverr (2019-01 – 2020-07)

• Transcribed and edited complex medical documentation with near-perfect accuracy.
• Annotated transcripts to support NLP model training and linguistic data organization.
• Applied knowledge of clinical communication and documentation standards (SOAP, EHR).
• Ensured data confidentiality and HIPAA compliance throughout transcription projects.

AI & Data Enthusiast (Project-Based Learning) (2020 – 2020)

• Completed applied projects on data labeling and categorization.
• Developed foundational understanding of AI-driven evaluation and annotation workflows.
• Practiced QA tracking and consistency verification in model training datasets.

MBBS – University of Benin (2022 – 2022)