Ellen Schafer

Key Skills

Software

Data Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Label Types

Entity Ner Classification

Segmentation

Data Collection

Freelancer Overview

I am a motivated and tech-savvy professional with hands-on experience in data annotation for AI model training across text, image, and audio formats. My background in Information Technology and Education Science, combined with my work as a freelancer, has given me a solid understanding of how to use AI tools like ChatGPT, Midjourney, and Claude for content creation, automation, and efficient data labeling. I am passionate about leveraging technology to enhance productivity and accuracy in AI training data projects. My strengths include strong analytical skills, attention to detail, and effective communication, allowing me to deliver high-quality annotated datasets that support machine learning and digital learning systems.

Labeling Experience

customer support sentiment and intent annotation project

Data Annotation TechTextEntity Ner ClassificationSegmentation

Role: Text Data Annotator Responsibilities: Reviewed customer chat transcripts and email conversations Assigned sentiment labels (Positive, Negative, Neutral) Classified customer intent using predefined taxonomy Tagged named entities such as Order IDs and Product Names Followed annotation guidelines and quality assurance standards Maintained minimum 95% inter-annotator agreement score Participated in weekly calibration sessions with QA team Tools & Workflow: Logged tasks and annotations in Labelbox Used Prodigy interface for entity-level tagging Followed version-controlled annotation guidelines Reported ambiguous cases to project manager

Role: Text Data Annotator Responsibilities: Reviewed customer chat transcripts and email conversations Assigned sentiment labels (Positive, Negative, Neutral) Classified customer intent using predefined taxonomy Tagged named entities such as Order IDs and Product Names Followed annotation guidelines and quality assurance standards Maintained minimum 95% inter-annotator agreement score Participated in weekly calibration sessions with QA team Tools & Workflow: Logged tasks and annotations in Labelbox Used Prodigy interface for entity-level tagging Followed version-controlled annotation guidelines Reported ambiguous cases to project manager

2025

Education

Work History