Comfort S.

Key Skills

Software

Appen

Data Annotation Tech

Mercor

Top Subject Matter

Computer vision image annotation for AI training

Natural language understanding (sentiment/intent/entity extraction)

Video understanding and object tracking for AI training

Top Data Types

Image

Text

Video

Top Task Types

Bounding Box

Entity (NER) Classification

Tracking

Freelancer Overview

Freelance Data Annotator (Remote) — Image projects (Bounding boxes and segmentation). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include N and A. Education includes Bachelor of Science, Federal University of Lafia. AI-training focus includes data types such as Image, Text, and Video and labeling workflows including Bounding Box, Entity (NER) Classification, and Tracking.

Labeling Experience

Freelance Data Annotator (Remote) — Video annotation projects

VideoTracking

Performed video annotation by tracking and labeling moving objects frame by frame. Produced consistent temporal labels to support training and evaluation of video understanding models. Followed strict instructions and reviewed work carefully to preserve accuracy. • Labeled moving objects across video frames • Maintained label consistency over time • Completed sequential tracking annotations • Applied detailed guidelines to reduce labeling errors

2024 - Present

Freelance Data Annotator (Remote) — Text annotation projects

TextEntity (NER) Classification

Annotated text data by tagging sentiment, intent, and key entities. Labeled reviews and conversations to help train AI to understand human language. Ensured high-quality outputs by carefully reviewing work against detailed instructions. • Tagged sentiment and intent labels • Labeled key entities in text • Annotated reviews and conversational data • Maintained accuracy through careful self-review

2024 - Present

Freelance Data Annotator (Remote) — Image projects (Bounding boxes and segmentation)

ImageBounding Box

Labeled image datasets by drawing bounding boxes around relevant objects, people, and environments. Performed object segmentation/precise outlining to ensure accurate spatial labeling for downstream AI training. Followed strict guidelines to maintain consistency and quality across tasks. • Drew bounding boxes for objects in images • Segmented objects with accurate boundaries • Reviewed outputs to keep accuracy above 98% • Met daily and weekly labeling targets

2024 - Present

Education

Work History