Israel Ibiyanmi

Detail-oriented and highly accurate Data Annotation Specialist with hands-on experience in labeling and quality-checking text, image, audio, and video datasets. Proven ability to maintain high throughput while delivering consistently precise annotations that power AI/ML models. Adept at transcription, content moderation, and quality assurance across multiple data modalities. Comfortable working independently in remote environments with strong communication and time-management skills.

Data Annotation Specialist at Outlier.ai (2023-01 – Present)

• Annotated large volumes of text, image, video, and audio data to train and evaluate machine learning models.
• Labeled entities, intent, sentiment, and relationships in NLP datasets with consistently high accuracy scores.
• Drew bounding boxes, polygons, and semantic segmentation masks on images and video frames for computer vision tasks.
• Transcribed audio recordings with precise timestamps and speaker identification for speech recognition models.
• Moderated content by flagging policy-violating material across text, image, and video datasets.
• Performed quality assurance reviews on peer annotations, identifying and correcting errors to maintain dataset integrity.
• Worked within platform guidelines to meet daily throughput targets while maintaining accuracy above benchmark thresholds.
• Collaborated asynchronously with remote team leads to clarify annotation guidelines and edge cases.
• Used Google Sheets and Excel to track annotation batches, log QA results, and report productivity metrics.

Bachelor of Science (B.Sc.) in Microbiology – Federal University of Agriculture, Abeokuta (FUNAAB)