Kayla Mccree

Key Skills

Software

Appen

Clickworker

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Text

Top Task Types

Computer Programming Coding

Data Collection

Object Detection

Prompt Response Writing SFT

Question Answering

Freelancer Overview

With a strong background in AI training and data labeling, I have honed my skills in content moderation, data annotation, and machine learning model refinement. As a Crowdsourced Labeler – Social Media Ads at Appen, I evaluate digital ads, assess their relevance, and contribute to AI model improvements with over 90% accuracy. My expertise extends to pattern recognition, data-driven decision-making, and AI-assisted content evaluation, ensuring precise and high-quality annotations. Beyond ad evaluation, my participation in AI-driven projects, including a hackathon where I contributed to UX design and website development, demonstrates my ability to integrate technology and user-centric design. My proficiency in programming languages like Python, JavaScript, and HTML, coupled with my PixieBrix Professional Certification, further enhances my technical acumen. With a keen eye for detail and adaptability, I excel in refining AI models, improving data quality, and ensuring high standards in AI training workflows.

Labeling Experience

Crowdsourced Labeler – Social Media Ads

AppenImageQuestion AnsweringText Summarization

• Evaluate and label social media advertisements to enhance AI-driven ad targeting and content moderation, maintaining a 90%+ accuracy rating to ensure high-quality data annotation for AI training. • Analyze ad relevance, accuracy, and appropriateness, identifying misleading or non-compliant content, and providing detailed feedback on user engagement patterns to refine AI recommendations. • Complete up to 60 ad assessments per batch within strict time constraints, optimizing data integrity and contributing to AI model refinement and automated decision-making.

• Evaluate and label social media advertisements to enhance AI-driven ad targeting and content moderation, maintaining a 90%+ accuracy rating to ensure high-quality data annotation for AI training. • Analyze ad relevance, accuracy, and appropriateness, identifying misleading or non-compliant content, and providing detailed feedback on user engagement patterns to refine AI recommendations. • Complete up to 60 ad assessments per batch within strict time constraints, optimizing data integrity and contributing to AI model refinement and automated decision-making.

2024

Education

Work History