Lucy Aroh

Key Skills

Software

Appen

Clickworker

CVAT

Labelbox

Label Studio

Remotasks

Toloka

Telus

Scale AI

Top Subject Matter

Nlp Domain Expertise

Computer Vision

Chatbots Domain Expertise

Top Data Types

Image

Text

Video

Document

Top Label Types

Bounding Box

Classification

Emotion Recognition

Evaluation Rating

Entity Ner Classification

Freelancer Overview

AI Data Annotator & Content Evaluator. Core strengths include Internal, Proprietary Tooling, and Appen. Education includes Bachelor of Science, University Of Nigeria (2023). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Entity (NER) Classification.

Labeling Experience

AI Data Annotator & Content Evaluator

Text

As an AI Data Annotator & Content Evaluator at InsightCore Analytics, I was responsible for annotating and labeling diverse datasets including text, images, and audio for both NLP and computer vision models. I ranked and evaluated AI-generated responses and contributed to high-impact prompt engineering for chatbot and recommendation system training. Multilingual annotation tasks were performed to ensure cultural accuracy for localized AI applications. • Labeled and evaluated over 10,000 data points monthly maintaining a 97% accuracy rate. • Generated prompts and feedback for model training, improving response quality. • Worked with global teams using Slack and Jira, reducing dataset errors. • Followed strict data privacy protocols and NDA compliance.

As an AI Data Annotator & Content Evaluator at InsightCore Analytics, I was responsible for annotating and labeling diverse datasets including text, images, and audio for both NLP and computer vision models. I ranked and evaluated AI-generated responses and contributed to high-impact prompt engineering for chatbot and recommendation system training. Multilingual annotation tasks were performed to ensure cultural accuracy for localized AI applications. • Labeled and evaluated over 10,000 data points monthly maintaining a 97% accuracy rate. • Generated prompts and feedback for model training, improving response quality. • Worked with global teams using Slack and Jira, reducing dataset errors. • Followed strict data privacy protocols and NDA compliance.

2024 - Present

AI Content Evaluator

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In the role of AI Content Evaluator, I conducted large-scale evaluation of search relevance and content quality for enterprise AI clients. Tasks included the semantic tagging and classification of queries and SERP results using proprietary platforms. I also contributed to identifying and reporting low-quality or biased outputs to enhance AI model refinement. • Analyzed over 1,500 responses monthly across customer support and social media topics. • Delivered improvements to model accuracy through intent classification and semantic tagging. • Streamlined evaluation workflows resulting in faster task completion. • Ensured timely delivery of high-quality datasets through remote collaboration.

In the role of AI Content Evaluator, I conducted large-scale evaluation of search relevance and content quality for enterprise AI clients. Tasks included the semantic tagging and classification of queries and SERP results using proprietary platforms. I also contributed to identifying and reporting low-quality or biased outputs to enhance AI model refinement. • Analyzed over 1,500 responses monthly across customer support and social media topics. • Delivered improvements to model accuracy through intent classification and semantic tagging. • Streamlined evaluation workflows resulting in faster task completion. • Ensured timely delivery of high-quality datasets through remote collaboration.

2023 - 2024

Junior Data Annotator

AppenTextEntity Ner Classification

As a Junior Data Annotator, I performed structured annotation for NLP datasets with a focus on intent classification, sentiment tagging, named entity recognition, and paraphrase grouping. This experience included both data labeling and contributing to quality assurance and workflow optimization. I also assisted in onboarding new team members by preparing guideline summaries for training purposes. • Processed over 8,000 data points with at least 95% accuracy. • Identified and corrected annotation errors to enhance data quality. • Proficient in tools such as Appen Connect and Prodigy. • Supported virtual training to improve overall team efficiency.

As a Junior Data Annotator, I performed structured annotation for NLP datasets with a focus on intent classification, sentiment tagging, named entity recognition, and paraphrase grouping. This experience included both data labeling and contributing to quality assurance and workflow optimization. I also assisted in onboarding new team members by preparing guideline summaries for training purposes. • Processed over 8,000 data points with at least 95% accuracy. • Identified and corrected annotation errors to enhance data quality. • Proficient in tools such as Appen Connect and Prodigy. • Supported virtual training to improve overall team efficiency.

2023 - 2023

Education

Work History