Joy Agu

Key Skills

Software

Mindrift

Appen

Clickworker

CVAT

Labelbox

Toloka

Telus

Top Subject Matter

Trajectory Data Quality Assurance

Image, Video, Text, and Audio Data Annotation

Text Domain Expertise

Top Data Types

Image

Text

Document

Top Task Types

Classification

Bounding Box

Polygon

Segmentation

Entity Ner Classification

Point Key Point

Object Detection

Text Generation

Question Answering

Text Summarization

RLHF

Transcription

Evaluation Rating

Data Collection

Freelancer Overview

Annotator & Data Labeling Specialist. Core strengths include Internal, Proprietary Tooling, and Mindrift. Education includes Bachelor of Science, National Open University of Nigeria (2025) and Diploma, Lagos State Polytechnic, Ikorodu (2023). AI-training focus includes data types such as Trajectory and Multimodal and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Freelance Data Annotator & Quality Reviewer

AppenClassification

Delivered annotation, quality scoring, and intent validation on text, audio, and image datasets across four leading annotation platforms. Flagged ambiguous cases and generated structured written reports to reduce team inconsistencies. Adapted swiftly to client-specific tools and project guidelines with no ramp-up errors. • Performed simultaneous work for Telus Digital, E2f, Appen, and Aurora. • Conducted fact validation and peer review tasks as part of quality workflows. • Maintained high consistency standards and output throughput over 2+ years. • Supported asynchronous operations across distributed global teams.

Delivered annotation, quality scoring, and intent validation on text, audio, and image datasets across four leading annotation platforms. Flagged ambiguous cases and generated structured written reports to reduce team inconsistencies. Adapted swiftly to client-specific tools and project guidelines with no ramp-up errors. • Performed simultaneous work for Telus Digital, E2f, Appen, and Aurora. • Conducted fact validation and peer review tasks as part of quality workflows. • Maintained high consistency standards and output throughput over 2+ years. • Supported asynchronous operations across distributed global teams.

2023 - Present

Annotator & Data Labeling Specialist

Validated annotation batches for correctness, completeness, and reproducibility on trajectory datasets. Maintained a 0% critical error rate throughout the contract period. Collaborated asynchronously with global teams to refine annotation and quality assurance guidelines. • Upheld strict compliance with annotation protocols for accurate data. • Reduced inter-annotator disagreements by contributing quality feedback. • Participated in guideline documentation and best practices recommendations. • Ensured reproducibility of all labeled output through structured reviews.

Validated annotation batches for correctness, completeness, and reproducibility on trajectory datasets. Maintained a 0% critical error rate throughout the contract period. Collaborated asynchronously with global teams to refine annotation and quality assurance guidelines. • Upheld strict compliance with annotation protocols for accurate data. • Reduced inter-annotator disagreements by contributing quality feedback. • Participated in guideline documentation and best practices recommendations. • Ensured reproducibility of all labeled output through structured reviews.

2025 - 2025

Data Annotation & AI Quality Assurance Specialist

MindriftClassification

Annotated and evaluated large-scale text, image, and multimedia datasets in technical domains. Broke down complex multi-step task instructions into structured annotation workflows to ensure guideline alignment and reproducibility. Ran A/B evaluations and reviewed LLM outputs for intent alignment, factual accuracy, and tone consistency. • Delivered consistent accuracy benchmarks over a 2-year period. • Managed annotation across multiple data types and labeling instructions. • Used browser-based tools and Linux-compatible environments for workflow execution. • Provided feedback that contributed to model improvements and training cycles.

Annotated and evaluated large-scale text, image, and multimedia datasets in technical domains. Broke down complex multi-step task instructions into structured annotation workflows to ensure guideline alignment and reproducibility. Ran A/B evaluations and reviewed LLM outputs for intent alignment, factual accuracy, and tone consistency. • Delivered consistent accuracy benchmarks over a 2-year period. • Managed annotation across multiple data types and labeling instructions. • Used browser-based tools and Linux-compatible environments for workflow execution. • Provided feedback that contributed to model improvements and training cycles.

2023 - 2025

Education

Work History