James A.

Key Skills

Software

Labelbox

CVAT

Supervisely

Label Studio

Appen

Other

Top Subject Matter

Medical imaging (X-rays, MRIs, CT scans)

radiology and diagnosis labels

Multilingual NLP datasets (sentiment and entity recognition)

Top Data Types

Text

Audio

Image

Top Task Types

Diagnosis

Transcription

Freelancer Overview

Data Labeling & AI Training Specialist (2013–Present) - Medical Data Labeling & QA. Core strengths include Labelbox, CVAT, and Supervisely. Education includes Bachelor of Science, Jomo Kenyatta University of Agriculture & Technology and Certified National Accountant, Association of National Accountants of Nigeria. AI-training focus includes data types such as Medical, DICOM, and Text and labeling workflows including Diagnosis, Entity (NER), and Transcription.

Labeling Experience

Data Labeling & AI Training Specialist (2013–Present) - Audio & Speech Transcription

OtherAudioTranscription

The role covered audio & speech recognition labeling, focusing on accurate transcription for training speech models. I transcribed audio datasets in English and African languages. I performed quality checks to maintain consistency and reduce annotation errors. • Transcribed audio datasets for speech recognition • Labeled speech content in English & African languages • Applied QA to verify transcription quality • Produced ready-to-train speech dataset outputs

2013 - Present

Data Labeling & AI Training Specialist (2013–Present) - Text Classification & Entity Labeling

Label StudioText

The role included text labeling for NLP model training, including sentiment and entity recognition tasks. I prepared multilingual datasets to support analysis such as sentiment classification. I ensured labels were consistent and suitable for model ingestion using dataset validation and QA processes. • Categorized multilingual text datasets for sentiment analysis • Labeled text entities for entity recognition • Performed quality assurance checks on annotations • Prepared datasets for NLP/healthcare and other downstream use cases

2013 - Present

Data Labeling & AI Training Specialist (2013–Present) - Medical Data Labeling & QA

LabelboxDiagnosis

The role involved medical data labeling and radiology annotation for diagnostic AI workflows. I annotated and QA-verified imaging data such as X-rays, MRIs, and CT scans. I applied standardized guidelines to reduce critical errors and improve consistency across annotators. • Labeled tumor detection and radiology findings • Annotated 200,000+ medical images with zero critical errors • QA-verified 500,000+ images with 98% accuracy • Designed annotation guidelines reducing inconsistencies by 40%

2013 - Present

Education

Work History