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Moses Omosa

Moses Omosa

Key Skills

Software

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Top Subject Matter

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Top Data Types

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Top Label Types

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Freelancer Overview

I am an analytical and detail-oriented Applied Mathematics student with hands-on experience in data analysis, content evaluation, and information verification. My background includes analyzing quantitative datasets, interpreting complex information, and producing structured outputs by following technical guidelines and ensuring quality control. I am skilled in data labeling, annotation, and validation, with a strong focus on logical reasoning, pattern recognition, and error detection. I am comfortable working with digital tools such as Microsoft Excel, Google Sheets, and various AI platforms. I thrive in remote environments, quickly adapt to new systems, and am passionate about supporting AI training and machine learning model improvement through high-quality data processing and annotation work.

Not specified

Labeling Experience

Academic Data Analysis Projects

TextClassification
Academic projects were completed analyzing and labeling datasets using mathematical and statistical methods. Patterns and trends within structured numerical data were identified to support model validation. Clear data findings and verified outputs were presented as part of the project deliverables. • Analyzed datasets for labeling tasks. • Used statistical reasoning for pattern recognition. • Verified numerical accuracy for AI model training. • Provided structured interpretations and reports.

Academic projects were completed analyzing and labeling datasets using mathematical and statistical methods. Patterns and trends within structured numerical data were identified to support model validation. Clear data findings and verified outputs were presented as part of the project deliverables. • Analyzed datasets for labeling tasks. • Used statistical reasoning for pattern recognition. • Verified numerical accuracy for AI model training. • Provided structured interpretations and reports.

Not specified

Data Review and Annotation Practice (Independent Projects)

TextClassification
This independent project involved evaluating written and numerical data for logical accuracy and consistency. Information was categorized following strict guidelines to support machine learning objectives. AI-generated responses were reviewed and errors or inconsistencies were identified and documented. • Evaluated and categorized data for quality annotation. • Followed structured guidelines for data labeling. • Reviewed outputs from AI models and flagged inaccuracies. • Maintained documentation for evaluation results.

This independent project involved evaluating written and numerical data for logical accuracy and consistency. Information was categorized following strict guidelines to support machine learning objectives. AI-generated responses were reviewed and errors or inconsistencies were identified and documented. • Evaluated and categorized data for quality annotation. • Followed structured guidelines for data labeling. • Reviewed outputs from AI models and flagged inaccuracies. • Maintained documentation for evaluation results.

Not specified

Education

K

Kirinyaga University

Bachelor of Education, Applied Mathematics and Physics

Bachelor of Education
Not specified

Work History

K

Kirinyaga University

Data Analyst (Academic Research)

Kirinyaga
2021 - 2023