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Henry U.

Henry U.

AI Trainer | Data Annotator | AI Model Evaluator | Entry-Level Cybersecurity Analyst | Remote task specialist

Nigeria flagEnugu, Nigeria

Key Skills

Software

No software listed

Top Subject Matter

Artificial Intelligence / Machine Learning
Cybersecurity / Information Security
Data Analysis / Research

Top Data Types

No data types listed

Top Task Types

No task types listed

Freelancer Overview

Experienced in AI training and data labeling tasks involving the evaluation, classification, and annotation of large datasets to improve machine learning model performance. Responsibilities included reviewing AI-generated outputs for accuracy, relevance, safety, and coherence based on strict project guidelines. Performed text classification, sentiment analysis, entity recognition, and content categorization across diverse datasets. Ensured high-quality annotations by carefully interpreting task instructions and maintaining consistency across labeling decisions. Participated in quality assurance checks by reviewing and correcting errors in previously labeled data to improve dataset reliability. Contributed to model training feedback loops by identifying incorrect or biased outputs and providing structured corrections. Developed strong attention to detail, analytical thinking, and the ability to work independently in remote environments. Gained experience using spreadsheet tools and annotation platforms to manage and complete tasks efficiently within deadlines. This experience strengthened skills in data interpretation, guideline adherence, and supporting AI system improvement through accurate human feedback and structured evaluation processes.

Labeling Experience

One AI training and data labeling experience involved working on text classification and AI response evaluation tasks fo

One AI training and data labeling experience involved working on text classification and AI response evaluation tasks for machine learning model improvement. In this role, I reviewed AI-generated answers and assessed them based on accuracy, relevance to the prompt, clarity, and safety guidelines. I also labeled datasets by categorizing text into predefined classes such as intent, sentiment, and topic type. During the task, I carefully followed detailed annotation guidelines to ensure consistency and reduce labeling errors. When evaluating AI responses, I identified issues such as incomplete answers, factual inconsistencies, or irrelevant content, and provided corrected labels or feedback to improve model training quality. I also performed quality checks on previously labeled data to ensure alignment with project standards. This experience strengthened my attention to detail, critical thinking, and ability to interpret complex instructions. It also improved my understanding of how human feedback directly contributes to enhancing AI model performance and reliability in real-world applications.

Not specified

Education

C

Cisco training program

Degree not specified

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Not specified

Work History

C

Company not specified

Based on your background (Microbiology student, ESUT, 1+ year AI training + cybersecurity learning), the **best single w

Location not specified
2025 - Present