Elizabeth Odeyemi

Key Skills

Software

Appen

Clickworker

CrowdSource

Remotasks

V7 Labs

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Document

Image

Text

Video

Top Label Types

Action Recognition

Audio Recording

Computer Programming Coding

Evaluation Rating

Object Detection

Question Answering

Text Generation

Text Summarization

Transcription

Translation Localization

Freelancer Overview

I am a dedicated and detail-oriented professional with a background in Electrical & Electronics Engineering and hands-on experience reviewing AI-generated responses. My experience as an AI Response Reviewer involved evaluating and improving the clarity and accuracy of AI outputs using structured guidelines, which has given me a strong foundation in data labeling and annotation for natural language processing tasks. I am a fast learner with solid computer skills, experience in Microsoft Word, and a proven ability to collaborate effectively within teams. I am eager to apply my analytical skills and technical mindset to contribute to high-quality AI training data projects.

Labeling Experience

AI Response Evaluation & Text Annotation Specialist

AppenAudioQuestion AnsweringText Generation

Worked on AI model improvement projects focused on evaluating and refining AI-generated responses. Reviewed pairs of responses using structured quality guidelines and assessed them for clarity, accuracy, relevance, coherence, instruction-following, and safety compliance. Ranked outputs based on predefined scoring rubrics and provided detailed justifications for evaluation decisions. Identified weaknesses such as incomplete answers, logical inconsistencies, vague explanations, or policy risks, and produced improved rewritten versions to enhance overall response quality. Contributed to improving model reliability, consistency, and alignment with user intent across various subject domains.

Worked on AI model improvement projects focused on evaluating and refining AI-generated responses. Reviewed pairs of responses using structured quality guidelines and assessed them for clarity, accuracy, relevance, coherence, instruction-following, and safety compliance. Ranked outputs based on predefined scoring rubrics and provided detailed justifications for evaluation decisions. Identified weaknesses such as incomplete answers, logical inconsistencies, vague explanations, or policy risks, and produced improved rewritten versions to enhance overall response quality. Contributed to improving model reliability, consistency, and alignment with user intent across various subject domains.

2025 - 2023

Education

Work History