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Paul Josiah (jaypee)

Paul Josiah (jaypee)

Data Annotation Specialist & NLP Researcher

Nigeria flagLagos, Nigeria
$10.00/hrIntermediateImeritLabel Studio

Key Skills

Software

iMeritiMerit
Label StudioLabel Studio

Top Subject Matter

Causal Relation Extraction in NLP
Agricultural Computer Vision (Crop Disease)

Top Data Types

TextText
ImageImage
DocumentDocument

Top Task Types

RelationshipRelationship
ClassificationClassification
Bounding BoxBounding Box
Fine-tuningFine-tuning
Computer Programming/CodingComputer Programming/Coding
Data CollectionData Collection

Freelancer Overview

Data Annotation Specialist & NLP Researcher, Edyah Consulting. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Engineering, University of Ibadan (2025) and Microsoft Certified: Azure Data Scientist Associate, Microsoft (2025). AI-training focus includes data types such as Text and Image and labeling workflows including Relationship and Classification.

IntermediateEnglishFrench

Labeling Experience

Data Annotation Specialist & NLP Researcher, Edyah Consulting

TextRelationship
Oversaw end-to-end annotation workflows for large-scale causal extraction datasets, including annotation guidelines design and taxonomy creation. Tagged and evaluated model-generated outputs using structured rubrics, assessing accuracy, relation classification, and boundary detection to improve model performance. Conducted error analysis and implemented quality improvements that increased inter-annotator agreement. • Designed annotation workflows and onboarding for multi-label schemas • Applied evaluation rubrics to tag and QA model outputs • Automated data-quality pipelines to enhance QA efficiency • Collaborated with ML engineers for model retraining and dataset refinement

Oversaw end-to-end annotation workflows for large-scale causal extraction datasets, including annotation guidelines design and taxonomy creation. Tagged and evaluated model-generated outputs using structured rubrics, assessing accuracy, relation classification, and boundary detection to improve model performance. Conducted error analysis and implemented quality improvements that increased inter-annotator agreement. • Designed annotation workflows and onboarding for multi-label schemas • Applied evaluation rubrics to tag and QA model outputs • Automated data-quality pipelines to enhance QA efficiency • Collaborated with ML engineers for model retraining and dataset refinement

2025 - Present

ML Data Specialist — Computer Vision, Zummit Africa

ImageClassification
Led dataset construction for crop-disease image classification by sourcing, curating, and labeling a large image set with clear class definitions. Conducted iterative quality reviews to resolve ambiguities and refined guidelines for consistent annotation. Developed data augmentation techniques guided by annotation outcome analysis. • Managed labeling of 5,000+ crop disease images • Applied structured class definitions and edge-case guidelines • Implemented targeted augmentation to decrease misclassification • Standardized labelling protocol handoff for workflow reproducibility

Led dataset construction for crop-disease image classification by sourcing, curating, and labeling a large image set with clear class definitions. Conducted iterative quality reviews to resolve ambiguities and refined guidelines for consistent annotation. Developed data augmentation techniques guided by annotation outcome analysis. • Managed labeling of 5,000+ crop disease images • Applied structured class definitions and edge-case guidelines • Implemented targeted augmentation to decrease misclassification • Standardized labelling protocol handoff for workflow reproducibility

2024 - 2025

Image Labelling Quality Framework Project

ImageClassification
Developed gold-standard benchmark datasets and assessment protocols for agricultural computer vision labeling tasks. Employed stratified sampling and accuracy tests to uphold consistency and maintain label accuracy above 95%. Established best practices for quality control and annotator assessment. • Constructed benchmark datasets for agricultural images • Devised protocols to assess annotator performance • Used sampling strategies for quality maintenance • Standardized workflows for improved production accuracy

Developed gold-standard benchmark datasets and assessment protocols for agricultural computer vision labeling tasks. Employed stratified sampling and accuracy tests to uphold consistency and maintain label accuracy above 95%. Established best practices for quality control and annotator assessment. • Constructed benchmark datasets for agricultural images • Devised protocols to assess annotator performance • Used sampling strategies for quality maintenance • Standardized workflows for improved production accuracy

Not specified

Causal Relation Annotation & Evaluation Project

TextRelationship
Constructed annotation pipelines for cause-effect relation extraction tasks, including cross-sentence and intra-sentence data. Developed custom evaluation suites to measure dataset quality and identify bottlenecks to refine annotation rubrics. Supported ongoing improvements in annotator training and dataset development. • Built pipelines to annotate causal relations • Created custom evaluation tools for precision and recall • Identified annotation-quality issues for targeted interventions • Enhanced rubric and workflow strategies for future projects

Constructed annotation pipelines for cause-effect relation extraction tasks, including cross-sentence and intra-sentence data. Developed custom evaluation suites to measure dataset quality and identify bottlenecks to refine annotation rubrics. Supported ongoing improvements in annotator training and dataset development. • Built pipelines to annotate causal relations • Created custom evaluation tools for precision and recall • Identified annotation-quality issues for targeted interventions • Enhanced rubric and workflow strategies for future projects

Not specified

Education

M

Microsoft

Microsoft Certified: Azure Data Scientist Associate, Data Science

Microsoft Certified: Azure Data Scientist Associate
2025 - 2025
U

University of Ibadan

Bachelor of Engineering, Industrial and Production Engineering

Bachelor of Engineering
2021 - 2025

Work History

E

Edyah Consulting

Data Annotation Specialist & NLP Researcher

Ibadan
2025 - Present
Z

Zummit Africa

Machine Learning Engineer

Lagos
2024 - 2025