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Label Studio
Data Annotation TechNo subject matter listed
Text
Image
Segmentation
ClassificationI have experience contributing to AI training data projects across multiple domains, including education, finance, politics, and travel. Through projects with Lunor AI, I labeled and reviewed educational content to support AI tutoring systems, converted political speeches into structured signals for analysis, curated market-moving financial events for AI models, and categorized Airbnb listings by trip type. These projects required strong attention to detail, consistency in annotation, data validation, and the ability to apply complex labeling guidelines accurately across large datasets. My work has been recognized through competitive AI data annotation challenges, including securing 2nd place in the TripFit Tags challenge. What distinguishes me is my ability to combine data labeling expertise with a broader data analytics background, enabling me to understand not only how to annotate data accurately but also how that data is ultimately used to train, evaluate, and improve machine learning models.
TextSegmentationHelped build a high-impact travel dataset by tagging Airbnb listings with who they’re best suited for (Solo, Couple, Family, Group, Business, etc.). Each task is a quick decision based on the listing’s name, description, property type, room type, and amenities.
