Lynn Gichuhi

Key Skills

Software

Supervisely

CrowdSource

CloudFactory

Clickworker

Labelbox

Mercor

Micro1

Top Subject Matter

Healthcare Data & Medical Documentation

Medical Imaging

AI for Community Health

Top Data Types

Image

Video

Text

Top Task Types

Classification

Bounding Box

Object Detection

Transcription

Evaluation/Rating

Prompt + Response Writing (SFT)

Segmentation

Freelancer Overview

Data Annotation Volunteer, AI for Community Health Initiative. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Supervisely. Education includes Bachelor of Science, Kisii University (2026) and Kenya Certificate of Secondary Education, Karima Girls High School (2021). AI-training focus includes data types such as Medical and DICOM and labeling workflows including Classification.

Labeling Experience

Data Annotation Volunteer, AI for Community Health Initiative

SuperviselyClassification

I labeled medical image datasets for a supervised classification model, maintaining a high degree of accuracy and consistency across a large number of samples. My role required a thorough and detail-oriented approach to properly annotate data crucial for model training. Collaboration with the technical team exposed me to the importance of data integrity and workflow documentation in annotation projects. • Maintained a 99% accuracy rate on medical image label assignments. • Collaborated with a technical team on data schema design and integration for annotation workflows. • Regularly flagged anomalies and ensured consistency through periodic review meetings. • Helped document workflows to uphold long-term reliability of dataset labels.

I labeled medical image datasets for a supervised classification model, maintaining a high degree of accuracy and consistency across a large number of samples. My role required a thorough and detail-oriented approach to properly annotate data crucial for model training. Collaboration with the technical team exposed me to the importance of data integrity and workflow documentation in annotation projects. • Maintained a 99% accuracy rate on medical image label assignments. • Collaborated with a technical team on data schema design and integration for annotation workflows. • Regularly flagged anomalies and ensured consistency through periodic review meetings. • Helped document workflows to uphold long-term reliability of dataset labels.

2024 - 2024

Education

Work History