Oluwapelumi Adewumi

Key Skills

Software

Appen

Clickworker

Top Subject Matter

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Top Data Types

Image

Top Label Types

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Freelancer Overview

I am a detail-oriented Data Annotation Specialist with hands-on experience delivering high-quality labeled datasets for AI and machine learning applications. My background includes annotating and reviewing large-scale text and image data for leading platforms such as Appen, Remotasks, and Atlas Capture, where I consistently maintained high accuracy and quality standards. I am skilled in following complex annotation guidelines, detecting errors, and providing actionable feedback to improve clarity and consistency. My expertise spans text classification, response evaluation, and data validation, with a strong focus on factual accuracy and data integrity. I thrive in remote, distributed QA teams, am adept at using web-based annotation tools and Google Workspace, and am comfortable handling sensitive data while adapting quickly to evolving project requirements.

Labeling Experience

image labelling

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Participated in an AI data annotation project focused on labeling and categorizing image datasets used to train and improve machine learning and computer vision models. The project involved accurately identifying objects, scenes, and visual elements within images according to predefined annotation guidelines and quality standards. Responsibilities included reviewing large volumes of images, applying labels and classification tags, ensuring dataset consistency, and maintaining high accuracy during annotation workflows. The work supported the development of AI systems used for image recognition, automation, and intelligent decision-making applications.

Participated in an AI data annotation project focused on labeling and categorizing image datasets used to train and improve machine learning and computer vision models. The project involved accurately identifying objects, scenes, and visual elements within images according to predefined annotation guidelines and quality standards. Responsibilities included reviewing large volumes of images, applying labels and classification tags, ensuring dataset consistency, and maintaining high accuracy during annotation workflows. The work supported the development of AI systems used for image recognition, automation, and intelligent decision-making applications.

2022 - 2023

Education

Work History