Benjamin K.

Key Skills

Software

Other

Data Annotation Tech

Top Subject Matter

AI/ML annotation quality assurance

EHR/healthcare AI scribing and labeling

Legal Services & Contract Review

Top Data Types

Image

Text

Document

Top Task Types

Classification

Freelancer Overview

Freelance Data Annotation and Labeling - Outlier AI / Prolific.com / Alignerr AI. Brings 10+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other and Data Annotation Tech. Education includes Diploma in Community Health Nursing Education, Maua Methodist School of Nursing (2015) and Bachelor of Science in Statistics and Programming, Kenyatta University (2017). AI-training focus includes data types such as Image, Medical, and DICOM and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Freelance Data Annotation and Labeling (Quality Control) - Outlier AI / Prolific.com / Alignerr AI

OtherImageClassification

Performed quality control evaluations of fellow annotators’ completed tasks to ensure consistency and accuracy against project guidelines. Evaluated AI outputs, prompts, and responses using predefined quality metrics and provided written feedback to annotators to resolve complex labeling issues. Executed pixel-level analysis and edge detection using optimized hyperparameters while tracking recall, precision, and accuracy for quality assurance. • Pixel-level image analysis and edge detection • QA reviews for inter-annotator consistency • Feedback loops to correct prompt/output alignment • Bias and overfitting checks during pattern identification

2023 - Present

Freelance EHR AI Scribe - Data Annotation Tech

Data Annotation Tech

Evaluated EHR AI scribe outputs for accuracy, safety, relevance, and regulatory compliance with HIPAA and GDPR. Applied data annotation standards and workflows to high-volume, complex EHR datasets, extracting clinical entities and medical keywords and assessing alignment to existing patient records. Reviewed outputs for context retention and utterance segmentation across speaker and multichannel differentiation axes. • HIPAA/GDPR-aligned evaluation of EHR AI outputs • Clinical entity/keyword extraction and alignment checks • Utterance segmentation and context retention review • Documented and transcribed patient records with reported accuracy and consistency targets

2025 - 2025

Education

Work History