Key Skills

Software

Remotasks

Top Subject Matter

AI Training and Evaluation

Academic Data Structuring

Text QA and Review

Top Data Types

Text

Document

Top Task Types

Text Summarization

Freelancer Overview

Self-Directed AI Literacy & Platform Familiarization. Core strengths include Remotasks, N, and A. Education includes Bachelor of Technology, Federal University of Technology, Minna (2024). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Text Summarization.

Labeling Experience

Self-Directed AI Literacy & Platform Familiarization

RemotasksText

This experience involved exploring popular AI training and annotation platforms and practising the rating of AI-generated responses. The focus was on assessing AI outputs for quality, accuracy, and guideline compliance, simulating real-world annotation workflows. Comprehensive familiarity was developed with rubric-driven evaluation processes and data labeling environments. • Evaluated AI-generated text for relevance, correctness, and adherence to detailed rubric instructions. • Investigated and practised annotation tasks on platforms like DataAnnotation, Outlier, and Remotasks. • Developed skill in understanding annotation guidelines, criteria, and edge cases unique to each platform. • Consistently simulated industry-standard QA and review tasks for AI training purposes.

This experience involved exploring popular AI training and annotation platforms and practising the rating of AI-generated responses. The focus was on assessing AI outputs for quality, accuracy, and guideline compliance, simulating real-world annotation workflows. Comprehensive familiarity was developed with rubric-driven evaluation processes and data labeling environments. • Evaluated AI-generated text for relevance, correctness, and adherence to detailed rubric instructions. • Investigated and practised annotation tasks on platforms like DataAnnotation, Outlier, and Remotasks. • Developed skill in understanding annotation guidelines, criteria, and edge cases unique to each platform. • Consistently simulated industry-standard QA and review tasks for AI training purposes.

2025 - Present

Peer Academic Review & Proofreading Initiative

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This initiative involved reviewing and editing peers' assignments, focusing on grammar, clarity, and factual consistency. It closely mirrored QA workflows used on AI training and data review platforms, emphasizing systematic quality assurance methods. A customized proofreading checklist was developed to ensure each document met high standards before submission. • Conducted detailed text reviews to identify and correct grammatical and logical errors. • Simulated annotation QA/rating by ensuring consistency and quality in text outputs. • Designed and implemented a quality control checklist for proofreading workflows. • Provided structured feedback consistent with AI content moderation tasks.

This initiative involved reviewing and editing peers' assignments, focusing on grammar, clarity, and factual consistency. It closely mirrored QA workflows used on AI training and data review platforms, emphasizing systematic quality assurance methods. A customized proofreading checklist was developed to ensure each document met high standards before submission. • Conducted detailed text reviews to identify and correct grammatical and logical errors. • Simulated annotation QA/rating by ensuring consistency and quality in text outputs. • Designed and implemented a quality control checklist for proofreading workflows. • Provided structured feedback consistent with AI content moderation tasks.

2024 - Present

Research Data Collection & Summarization

TextText Summarization

As part of an academic research project, I collected, organized, and summarized qualitative and quantitative text data. The experience emphasized formatting and consistently labeling raw information, ensuring accuracy and coherence across categories. This simulated foundational data annotation processes involving large text volumes. • Gathered research data from academic sources and categorized it with clear, consistent labeling. • Maintained accuracy and coherence in summarizing and structuring text data. • Demonstrated ability to manage repetitive text-based tasks similar to annotation work. • Practised disciplined review and accuracy standards for structured information handling.

As part of an academic research project, I collected, organized, and summarized qualitative and quantitative text data. The experience emphasized formatting and consistently labeling raw information, ensuring accuracy and coherence across categories. This simulated foundational data annotation processes involving large text volumes. • Gathered research data from academic sources and categorized it with clear, consistent labeling. • Maintained accuracy and coherence in summarizing and structuring text data. • Demonstrated ability to manage repetitive text-based tasks similar to annotation work. • Practised disciplined review and accuracy standards for structured information handling.

2024 - 2024

Education

Work History