Matthew Mcneely

Key Skills

Software

Appen

Telus

Top Subject Matter

AI model training

digital content

enterprise technology

Top Data Types

Text

Document

Top Task Types

Classification

RLHF

Evaluation/Rating

Data Collection

Text Generation

Freelancer Overview

AI Data Specialist. Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Appen and Telus. Education includes Master of Science, Georgia Institute of Technology (2015) and Bachelor of Science, Georgia Institute of Technology (2011). AI-training focus includes data types such as Text and labeling workflows including Classification, Evaluation, and Rating.

Labeling Experience

AI Data Specialist

AppenTextClassification

As an AI Data Specialist at Outlier, I delivered structured annotation, content labeling, and quality evaluation for multiple AI training projects. I reviewed, annotated, and categorized high volumes of digital records while ensuring alignment with complex, evolving rubrics. My work included surfacing edge cases and surpassing strict productivity and accuracy benchmarks.• Reviewed and verified over 8,000 digital text records for completeness and precision • Consistently applied multi-layered guidelines and classification schemas to annotation tasks • Identified and escalated 150+ ambiguous or edge-case content entries • Collaborated remotely to improve turnaround time on dispute resolution

As an AI Data Specialist at Outlier, I delivered structured annotation, content labeling, and quality evaluation for multiple AI training projects. I reviewed, annotated, and categorized high volumes of digital records while ensuring alignment with complex, evolving rubrics. My work included surfacing edge cases and surpassing strict productivity and accuracy benchmarks.• Reviewed and verified over 8,000 digital text records for completeness and precision • Consistently applied multi-layered guidelines and classification schemas to annotation tasks • Identified and escalated 150+ ambiguous or edge-case content entries • Collaborated remotely to improve turnaround time on dispute resolution

2021 - Present

Content Moderator & Evaluation Analyst

TelusText

As a Content Moderator & Evaluation Analyst at TELUS International, I systematically evaluated user-generated content against strict multi-tiered policy frameworks. My role emphasized identifying borderline and edge-case materials and executing detailed documentation for each decision. This process drove updates to review guidelines and supported AI training workflows crucial to moderation quality.• Evaluated over 180,000 pieces of digital user-generated text content for compliance • Created and maintained structured decision logs used in several audit cycles • Designed reference checklists and decision trees to increase review accuracy • Accurately escalated nuanced content cases, supporting guideline improvements

As a Content Moderator & Evaluation Analyst at TELUS International, I systematically evaluated user-generated content against strict multi-tiered policy frameworks. My role emphasized identifying borderline and edge-case materials and executing detailed documentation for each decision. This process drove updates to review guidelines and supported AI training workflows crucial to moderation quality.• Evaluated over 180,000 pieces of digital user-generated text content for compliance • Created and maintained structured decision logs used in several audit cycles • Designed reference checklists and decision trees to increase review accuracy • Accurately escalated nuanced content cases, supporting guideline improvements

2017 - 2021

Education

Work History