I’m an experienced Data Annotation Specialist with over two years of hands-on work supporting AI and machine learning projects through platforms like Crowdgen and Outlier. My experience covers audio transcription, data labeling, and quality review, where I’ve helped ensure data accuracy and consistency across large-scale projects.
With an academic background in Public Health, I’ve developed strong attention to detail and a methodical approach to every task I take on. I’ve collaborated with linguists and engineers to improve annotation standards, worked on speech-to-text and sentiment analysis projects, and contributed to training data for large language models.
I’m confident using tools such as Labelbox, SuperAnnotate, and Google Workspace, and I enjoy remote teamwork just as much as independent work. I take pride in meeting deadlines, following clear guidelines, and helping deliver high-quality data that supports meaningful innovation in technology.
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