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Anjeline Ogonda

Anjeline Ogonda

AI Data Labeling Expert | 2D/3D Annotation | Quality-Driven

Kenya flagNairobi, Kenya
$4.00/hrExpertCloudfactoryCVATLabelbox

Key Skills

Software

CloudFactoryCloudFactory
CVATCVAT
LabelboxLabelbox
SamaSama
SuperAnnotateSuperAnnotate
TelusTelus

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor
ImageImage
VideoVideo

Top Task Types

Bounding Box
Classification
Cuboid
Polygon
Polyline

Freelancer Overview

I am a detail-oriented Data Annotation Specialist with over two years of hands-on experience in labeling and preparing high-quality training datasets for AI and machine learning models. My work has supported complex projects in autonomous vehicle systems, e-commerce, and natural language processing. I have annotated 2D, 3D, and BEV data using tools like CVAT, Supervisely, and Labelbox, with a focus on accuracy, consistency, and adherence to project guidelines. My time at Digital Divide Data and Samasource sharpened my ability to meet strict quality assurance standards and collaborate with remote QA teams efficiently. What sets me apart is my dual experience as both a data annotator and a quality analyst, allowing me to deliver clean datasets and provide critical feedback to improve team performance. I’m certified in clear communication and bring a strong foundation in computer science, which helps me understand the AI models that rely on the data I help shape. I take pride in delivering annotation work that directly contributes to smarter, more reliable AI systems.

ExpertEnglish

Labeling Experience

CVAT

Image segmentation

CVATImageSegmentation
Project Description – Aya Data (CVAT Annotation Project) At Aya Data, I contributed to a computer vision project focused on generating high-quality training data for autonomous systems. Using CVAT, I performed detailed annotations on image and video datasets, including object detection with bounding boxes, polygon segmentation, and frame-by-frame tracking. The datasets primarily involved urban environments, where precision in labeling vehicles, pedestrians, road signs, and lane markings was critical. My role required strong attention to detail, a deep understanding of annotation guidelines, and consistent communication with the QA team to ensure all data met client standards. I also helped flag edge cases and inconsistencies, which improved dataset quality and annotation workflow efficiency. The experience strengthened my skills in visual data analysis, annotation tool usage, and remote team collaboration.

Project Description – Aya Data (CVAT Annotation Project) At Aya Data, I contributed to a computer vision project focused on generating high-quality training data for autonomous systems. Using CVAT, I performed detailed annotations on image and video datasets, including object detection with bounding boxes, polygon segmentation, and frame-by-frame tracking. The datasets primarily involved urban environments, where precision in labeling vehicles, pedestrians, road signs, and lane markings was critical. My role required strong attention to detail, a deep understanding of annotation guidelines, and consistent communication with the QA team to ensure all data met client standards. I also helped flag edge cases and inconsistencies, which improved dataset quality and annotation workflow efficiency. The experience strengthened my skills in visual data analysis, annotation tool usage, and remote team collaboration.

2024

Education

L

Laikipia University

Bachelor of Education, Education

Bachelor of Education
2015 - 2019

Work History

D

Digital Divide Data

Quality Analyst

Nairobi
2024 - 2024