Emmanuel Etwapat

Key Skills

Software

Mercor

Top Subject Matter

No subject matter listed

Top Data Types

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Top Label Types

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Freelancer Overview

I am a detail-oriented IT graduate with over 5 years of professional experience in client support, data quality review, and digital operations. My recent work as a freelance microtask contributor involved accurate labeling and annotation of images and videos, consistently meeting deadlines and maintaining high-quality standards on platforms like Mercor. I excel at following detailed instructions, adapting quickly to new guidelines, and ensuring data integrity through precise documentation. My background in empathetic communication, response evaluation, and guideline adherence has equipped me to handle sensitive information and nuanced content, particularly in domains like medical insurance and customer engagement. I am proficient with digital tools, advanced in Microsoft Office, and comfortable navigating various IT platforms, making me well-suited for remote data labeling and AI training data roles that require analytical thinking, attention to detail, and reliable performance.

Labeling Experience

Data Labeller / Data Annotation Specialist (Remote)

MercorTextEvaluation Rating

I performed high-quality data annotation and labeling of diverse datasets, including text, reasoning chains, and model-generated responses to train advanced AI models. This involved human preference ranking, side-by-side comparisons, and evaluation of AI outputs for accuracy, coherence, and improvement opportunities. I consistently maintained annotation quality and adapted to evolving guidelines across multiple projects and domains. • Labeled text, reasoning, and multimodal content for AI model training • Applied detailed taxonomies and project specific instructions • Provided feedback to AI research teams for model alignment • Ensured high throughput while maintaining accuracy and consistency

I performed high-quality data annotation and labeling of diverse datasets, including text, reasoning chains, and model-generated responses to train advanced AI models. This involved human preference ranking, side-by-side comparisons, and evaluation of AI outputs for accuracy, coherence, and improvement opportunities. I consistently maintained annotation quality and adapted to evolving guidelines across multiple projects and domains. • Labeled text, reasoning, and multimodal content for AI model training • Applied detailed taxonomies and project specific instructions • Provided feedback to AI research teams for model alignment • Ensured high throughput while maintaining accuracy and consistency

2026

Education

Work History