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J
John Darren

John Darren

AI Agent Evaluation Analyst - Technology & Internet

USA flagKAPLAN, Usa
$100.00/hrExpertData Annotation Tech

Key Skills

Software

Data Annotation TechData Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage

Top Task Types

Bounding BoxBounding Box
PolygonPolygon
PolylinePolyline
Entity (NER) ClassificationEntity (NER) Classification
SegmentationSegmentation

Freelancer Overview

I am a detail-oriented professional with hands-on experience in AI agent evaluation, data annotation, and the analysis of complex systems. My background includes developing and applying systematic frameworks to assess AI model outputs, identify contradictions, and spot ambiguities, particularly in natural language processing and scenario-based projects. I am proficient in Python and familiar with data formats like JSON and YAML, allowing me to efficiently parse, clean, and interpret large datasets. My work has ranged from image reviewing to structured data analysis, where I have contributed to improving AI model accuracy and reliability. I excel at delivering clear technical documentation and structured feedback, ensuring quality and clarity in every project I undertake.

ExpertEnglish

Labeling Experience

Data Annotation Tech

Microsoft Ai image annotation

Data Annotation TechImageBounding BoxPolygon
Performing precise data annotation for computer vision models, creating high-quality training datasets that directly improved model accuracy and performance. · Expertly labeled thousands of images using techniques such as bounding boxes, semantic segmentation, and keypoint annotation to identify and delineate objects, scenes, and features. · Applied strict labeling guidelines to ensure consistency and reliability across datasets, contributing to robust model training for applications in [mention field, e.g., autonomous vehicles, medical imaging, or e-commerce]. · Participated in quality assurance cycles, reviewing peer annotations and refining labeling protocols to enhance dataset integrity and inter-annotator agreement. · Collaborated with data scientists and engineers to clarify edge cases and adapt annotation strategies, bridging the gap between project requirements and practical data preparation.

Performing precise data annotation for computer vision models, creating high-quality training datasets that directly improved model accuracy and performance. · Expertly labeled thousands of images using techniques such as bounding boxes, semantic segmentation, and keypoint annotation to identify and delineate objects, scenes, and features. · Applied strict labeling guidelines to ensure consistency and reliability across datasets, contributing to robust model training for applications in [mention field, e.g., autonomous vehicles, medical imaging, or e-commerce]. · Participated in quality assurance cycles, reviewing peer annotations and refining labeling protocols to enhance dataset integrity and inter-annotator agreement. · Collaborated with data scientists and engineers to clarify edge cases and adapt annotation strategies, bridging the gap between project requirements and practical data preparation.

2025

Education

S

San Francisco Bay University

Bachelor of Science, Data Analytics

Bachelor of Science
2018 - 2022

Work History

O

Outlier AI

Data Analyst and AI Project Consultant

Liebig
2024 - Present
F

Freelance

Data Analysis Consultant

Liebig
2022 - 2023