Oginni O.

Key Skills

Software

Labelbox

Toloka

Mercor

Top Subject Matter

AI response evaluation

linguistic/semantic dataset annotation

dataset cleaning and validation

Top Data Types

Text

Image

Document

Top Task Types

Entity (NER) Classification

Classification

Text Generation

Freelancer Overview

AI Generalist & Dataset Analyst (Freelance). Core strengths include N, A, and Labelbox. Education includes Doctor of Philosophy, Obafemi Awolowo University (2023) and Master of Science, Obafemi Awolowo University (2019). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Entity (NER) Classification.

Labeling Experience

Senior AI Data Annotation Specialist (Remote)

LabelboxTextClassification

Annotated and validated large-scale multimodal datasets for AI training, focusing on high-precision labeling under strict quality guidelines. Designed and refined annotation taxonomies to improve labeling efficiency while maintaining benchmark-level accuracy. Identified and flagged critical inconsistencies that contributed to measurable model performance improvements through rigorous guideline adherence.• Annotated and validated 500,000+ text and image data points.• Achieved 99.3% annotation accuracy and exceeded quality benchmarks.• Improved labeling efficiency by 35% via refined taxonomy design.• Led peer review sessions and flagged inconsistencies to improve model performance by 18%.

2026 - Present

AI Generalist & Dataset Analyst (Freelance)

Text

Performed AI response evaluation and correctness checking across high-volume datasets used for AI training. Applied complex rubrics to annotate linguistic and semantic data for model readiness and quality. Reduced dataset noise through systematic error detection and ambiguity review for improved downstream performance.• Applied rubrics for linguistic/semantic annotation and QA-style evaluation.• Evaluated AI-generated responses for correctness, bias, and ambiguity.• Reduced dataset noise by 40% using structured error detection.• Delivered high-quality outputs under tight deadlines.

2023 - 2025

Research Assistant (AI & Data Systems)

TextEntity (NER) Classification

Conducted research and development work focused on improving labeling accuracy and AI model reliability for training data workflows. Developed frameworks for multi-level classification and tagging schemes to support consistent dataset labeling. Collaborated on dataset validation processes to ensure annotation consistency and quality improvements.• Researched data labeling accuracy and model reliability topics.• Built multi-level classification/tagging frameworks for datasets.• Published research on improving annotation consistency.• Collaborated cross-functionally on dataset validation.

2022 - 2023

Education

Work History