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Mayo Boy

Mayo Boy

Lecturer - Cancer Research and Drug Therapeutics

Nigeria flagIbadan, Nigeria
$10.00/hrEntry LevelMercorImeritMicro1

Key Skills

Software

MercorMercor
iMeritiMerit
Micro1
Data Annotation TechData Annotation Tech
AppenAppen

Top Subject Matter

No subject matter listed

Top Data Types

AudioAudio
TextText
ImageImage

Top Task Types

Text GenerationText Generation
TranscriptionTranscription
PolygonPolygon
Bounding BoxBounding Box
Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)

Freelancer Overview

I am a detail-oriented professional with a strong background in laboratory sciences, data entry, and quality assurance, particularly within medical and scientific domains. My experience includes collecting, labeling, and sorting biological samples, ensuring precise data annotation and accurate record-keeping for diagnostic and research purposes. I am proficient in using Laboratory Information Systems (LIS) and Microsoft Office Suite to manage and organize large datasets, and I have a proven ability to follow strict compliance and quality control protocols. My analytical skills and commitment to accuracy make me well-suited for roles involving data labeling and AI training data, especially in healthcare, biochemistry, and environmental monitoring contexts.

Entry LevelYorubaEnglish

Labeling Experience

PROMPT ANNOTATOR

TextText Generation
In this position, I design and annotate prompts that guide AI systems to generate appropriate and contextually relevant responses. This includes categorizing prompt types, identifying intent, and ensuring consistency in tone, structure, and difficulty level. I also evaluate model outputs against expected responses, flagging errors and suggesting improvements to enhance model performance. Attention to detail is critical, as even small inconsistencies in prompt structure or labeling can affect training outcomes. The role requires strong language skills, critical thinking, and the ability to interpret complex guidelines. Collaboration with linguists, data scientists, and quality assurance teams is essential to maintain high annotation standards. Through this role, I contribute to improving the accuracy, safety, and usability of AI systems, ensuring they can effectively understand and respond to a wide range of human inputs.

In this position, I design and annotate prompts that guide AI systems to generate appropriate and contextually relevant responses. This includes categorizing prompt types, identifying intent, and ensuring consistency in tone, structure, and difficulty level. I also evaluate model outputs against expected responses, flagging errors and suggesting improvements to enhance model performance. Attention to detail is critical, as even small inconsistencies in prompt structure or labeling can affect training outcomes. The role requires strong language skills, critical thinking, and the ability to interpret complex guidelines. Collaboration with linguists, data scientists, and quality assurance teams is essential to maintain high annotation standards. Through this role, I contribute to improving the accuracy, safety, and usability of AI systems, ensuring they can effectively understand and respond to a wide range of human inputs.

2026 - Present

IMAGE ANNOTATOR

ImageBounding Box
This project focused on the preparation of high-quality annotated image datasets to train and validate computer vision models. The primary objective was to accurately label visual elements within large volumes of images to enable machines to recognize and interpret objects, scenes, and patterns. As an Image Annotator, I was responsible for performing tasks such as bounding box annotation, polygon segmentation, and image classification based on detailed client guidelines. The project required consistent application of annotation standards to ensure dataset uniformity and reliability. I worked with diverse image categories, including everyday objects, human activities, and environmental scenes. A key aspect of the project involved quality control and iterative improvement. Annotations were regularly reviewed, and feedback was incorporated to maintain high accuracy levels. Collaboration with team members and adherence to strict deadlines ensured timely project delivery. The final annotated dataset contributed directly to the training of AI models used in applications such as object detection, facial recognition, and automated image analysis, enhancing their performance and real-world usability.

This project focused on the preparation of high-quality annotated image datasets to train and validate computer vision models. The primary objective was to accurately label visual elements within large volumes of images to enable machines to recognize and interpret objects, scenes, and patterns. As an Image Annotator, I was responsible for performing tasks such as bounding box annotation, polygon segmentation, and image classification based on detailed client guidelines. The project required consistent application of annotation standards to ensure dataset uniformity and reliability. I worked with diverse image categories, including everyday objects, human activities, and environmental scenes. A key aspect of the project involved quality control and iterative improvement. Annotations were regularly reviewed, and feedback was incorporated to maintain high accuracy levels. Collaboration with team members and adherence to strict deadlines ensured timely project delivery. The final annotated dataset contributed directly to the training of AI models used in applications such as object detection, facial recognition, and automated image analysis, enhancing their performance and real-world usability.

2026 - 2026

Education

U

University of Medical Sciences, Ondo

Master of Science, Biochemistry

Master of Science
2025 - 2025
U

University of Medical Sciences, Ondo

Bachelor of Science, Biochemistry

Bachelor of Science
2019 - 2023

Work History

T

Timi Agabale Grammar School

Secondary School Teacher

Ede
2024 - Present
M

MMM Catholic Hospital

Medical Laboratory Scientist

Ibadan
2023 - 2023