Iyanuoluwa Obasa

Key Skills

Software

Labelbox

CVAT

Prodigy

Scale AI

Appen

Top Subject Matter

Medical Imaging

Radiology Domain Expertise

Healthcare AI

Top Data Types

Text

Image

Document

Top Task Types

Segmentation

Entity (NER) Classification

Freelancer Overview

Medical Image Annotation & AI Data Labeling Specialist. Brings 11+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, CVAT, and Prodigy. Education includes Bachelor of Medicine, Bachelor of Surgery, Ekiti State University (2023) and Diploma in General Nursing, Ekiti State University (2014). AI-training focus includes data types such as Medical, DICOM, and Text and labeling workflows including Segmentation and Entity (NER) Classification.

Labeling Experience

NLP Data Annotator and AI Evaluation Specialist

LabelboxTextEntity Ner Classification

Worked on text labeling and entity recognition tasks for natural language processing model training. Involved in sentiment classification and evaluation of AI-generated text for healthcare domain data. Participated in quality assurance and annotation guideline development for text-based datasets. • Labeled clinical and scientific documents for entities and key information extraction. • Assessed inter-rater reliability and ensured consistently high annotation quality. • Provided feedback on natural language outputs using RLHF strategies. • Applied annotation protocols for privacy and compliance, including de-identification.

Worked on text labeling and entity recognition tasks for natural language processing model training. Involved in sentiment classification and evaluation of AI-generated text for healthcare domain data. Participated in quality assurance and annotation guideline development for text-based datasets. • Labeled clinical and scientific documents for entities and key information extraction. • Assessed inter-rater reliability and ensured consistently high annotation quality. • Provided feedback on natural language outputs using RLHF strategies. • Applied annotation protocols for privacy and compliance, including de-identification.

Present

Medical Image Annotation & AI Data Labeling Specialist

LabelboxSegmentation

Specialized in medical image annotation across X-rays, CT scans, and ultrasounds, adhering to DICOM standards. Executed structured reporting and annotation to enhance machine learning dataset quality in healthcare. Conducted quality assurance, inter-rater reliability, and annotation guideline development for clinical AI applications. • Performed semantic segmentation and bounding box labeling using industry-leading software. • Validated AI-generated content and provided RLHF feedback for accuracy improvement. • Labeled and classified medical images for diagnosis and decision support system training. • Used Labelbox, CVAT, Prodigy, and Scale AI for annotation workflows and tool optimization.

Specialized in medical image annotation across X-rays, CT scans, and ultrasounds, adhering to DICOM standards. Executed structured reporting and annotation to enhance machine learning dataset quality in healthcare. Conducted quality assurance, inter-rater reliability, and annotation guideline development for clinical AI applications. • Performed semantic segmentation and bounding box labeling using industry-leading software. • Validated AI-generated content and provided RLHF feedback for accuracy improvement. • Labeled and classified medical images for diagnosis and decision support system training. • Used Labelbox, CVAT, Prodigy, and Scale AI for annotation workflows and tool optimization.

Present

Education

Work History