Daniel Maina

AI Data Annotator and AI training professional with 3 years of remote experience across Atlas AI and Remotasks. Experienced in labeling and classifying datasets, reviewing AI-generated content, evaluating data against task criteria, identifying errors and inconsistencies, and applying project instructions consistently. Comfortable with high-volume, guideline-driven tasks that require accuracy, concentration, independent judgment, and reliable turnaround.

Am undertaking a Data Wrangling and SQL which gives me the ability to work effectively.

Data Annotator / AI Training Specialist at ATLAS AI / AI DATA PROJECTS (2024-01 – Present)

• Label, classify, and organize AI training data using project-specific annotation rules and quality criteria.
• Review text, images, documents, and digital content to determine whether data meets defined task requirements.
• Evaluate AI-related datasets and flag incorrect, inconsistent, incomplete, or ambiguous information for review.
• Apply detailed instructions consistently across high-volume tasks while maintaining accuracy and data quality.
• Adapt to new annotation workflows, project guidelines, platforms, and task formats with minimal supervision.

AI Data Annotator / Data Labeling Specialist at REMOTASKS (2023-01 – 2025-12)

• Completed AI data labeling and training tasks using detailed project instructions and acceptance criteria.
• Classified datasets, reviewed information for relevance, and performed quality-control checks before task submission.
• Identified labeling errors and inconsistencies and corrected work according to applicable project rules.
• Managed independent remote workloads and deadlines across repetitive, high-volume annotation tasks.
• Adjusted quickly to changing task requirements, annotation processes, and project expectations.

Data Wrangling and SQL – Nashua Community College