Larry P.

Key Skills

Software

Labelbox

Top Subject Matter

Finance - Tax Evaluation

Finance - Customer Support

Top Data Types

Text

Top Task Types

Text Generation

Evaluation/Rating

Data Collection

Freelancer Overview

I am a Mathematics graduate with over one year of specialized experience in AI data labeling and response evaluation, having processed 5,000+ data points across diverse domains including general knowledge assessment, regulatory compliance, mathematical content, and customer service quality rating. As an AI Data Labeling Specialist, I consistently maintained a 98% inter-rater reliability score while evaluating AI generated responses for accuracy, helpfulness, harmlessness, and coherence using standardized rubrics. My work involved applying complex annotation guidelines with precision, identifying edge cases, providing detailed feedback for model improvement, and performing quality assurance reviews to ensure consistency across large scale datasets. What sets me apart is my mathematical foundation combined with practical annotation expertise. My degree in Mathematics provides me with strong logical reasoning, statistical analysis skills, and pattern recognition abilities that are essential for nuanced AI evaluation work. I excel at identifying subtle differences in response quality, maintaining high accuracy even with repetitive tasks, and quickly adapting to new domains and annotation frameworks. My experience spans prompt response assessment, data validation, comparative evaluation of model outputs, and edge case identification, all while working independently and meeting strict deadlines with minimal supervision. This unique combination of analytical rigor and hands on AI training experience enables me to deliver consistent, high quality annotations that directly improve model performance.

Labeling Experience

Data Engineer

TextData Collection

As an AI Data Labeling Specialist, I consistently maintained a 98% inter-rater reliability score while evaluating AI generated responses for accuracy, helpfulness, harmlessness, and coherence using standardized rubrics. My work involved applying complex annotation guidelines with precision, identifying edge cases, providing detailed feedback for model improvement, and performing quality assurance reviews to ensure consistency across large scale datasets.

2022 - 2023

Education

Work History