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K

Kelvin Anyanje

Data Annotation Specialist

USA flagRemote, Usa
ExpertLabelbox

Key Skills

Software

LabelboxLabelbox

Top Subject Matter

AI/ML Dataset Annotation
Legal Services & Contract Review
Regulatory Compliance & Risk Analysis

Top Data Types

ImageImage
TextText
DocumentDocument

Top Task Types

ClassificationClassification

Freelancer Overview

Data Annotation Specialist. Brings 7+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Labelbox. Education includes Master of Science, University of Maryland, College Park (2024) and Bachelor of Science, University of Maryland, College Park (2022). AI-training focus includes data types such as Image and labeling workflows including Classification.

Expert

Labeling Experience

Labelbox

Data Annotation Specialist

LabelboxImageClassification
As a Data Annotation Specialist, I annotated and labeled large-scale datasets for various AI/ML training tasks, including image classification, text categorization, entity recognition, and sentiment labeling. I ensured high quality and accuracy in the labeled datasets by reviewing and validating annotated data in line with project guidelines. I collaborated remotely with engineers to develop annotation schemas and addressed data ambiguities as needed. • Used platforms such as Labelbox, Scale AI, and proprietary tools to efficiently manage annotation workflows. • Delivered clean datasets that improved downstream model performance metrics by 20%. • Maintained 98%+ accuracy rate in all labeling projects, reducing error rates by 15%. • Focused on image, text, and entity-level annotations for state-of-the-art AI development.

As a Data Annotation Specialist, I annotated and labeled large-scale datasets for various AI/ML training tasks, including image classification, text categorization, entity recognition, and sentiment labeling. I ensured high quality and accuracy in the labeled datasets by reviewing and validating annotated data in line with project guidelines. I collaborated remotely with engineers to develop annotation schemas and addressed data ambiguities as needed. • Used platforms such as Labelbox, Scale AI, and proprietary tools to efficiently manage annotation workflows. • Delivered clean datasets that improved downstream model performance metrics by 20%. • Maintained 98%+ accuracy rate in all labeling projects, reducing error rates by 15%. • Focused on image, text, and entity-level annotations for state-of-the-art AI development.

2023 - Present

Education

U

University of Maryland, College Park

Master of Science, Computer Science

Master of Science
2022 - 2024
U

University of Maryland, College Park

Bachelor of Science, Economics and Statistics

Bachelor of Science
2018 - 2022

Work History

F

Freelance

AI Developer & Data Analyst

Remote
2022 - Present
U

University of Maryland

Data Science Research Assistant

College Park
2020 - 2022