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Label Studio
Dataloop
CVAT
Image
Polygon
Classification
Polyline
SegmentationI have over two years of hands-on experience in data labeling and AI training data preparation, specializing in image annotation (bounding boxes, polygons, segmentation) and text categorization for NLP models. At my previous role with a computer vision project, I consistently achieved 98% inter-annotator agreement by implementing clear style guides and quality checks. My ability to identify and flag ambiguous data edge cases—such as occluded objects or sarcastic text—reduced model error rates and retraining cycles What sets me apart is my focus on iterative feedback loops: I collaborated directly with ML engineers to refine labeling rules based on model performance, cutting rework by 30%. I’m also proficient with tools like Labelbox, CVAT, and custom Python scripts for quality assurance. Additionally, I’ve trained and mentored small annotation teams, emphasizing consistency, speed, and ethical data handling—ensuring diverse, representative datasets that mitigate bias in production models.
Geospatial Tiled Imagery
Data CollectionLabeled 10000+ hotel reviews for aspect-based sentiment analysis – enabling an OTA to show "why guests loved this property" (pool, breakfast, location) vs. "what needs improvement" (noise, outdated rooms). Classified 10000+ user search queries into 40+ intent categories – helping a travel app understand whether someone wants "budget hostels near nightlife" vs. "luxury resorts with kids' clubs.
Certificate, Cybersecurity
Bachelor of Arts, Philosophy and Religious Studies
Travel and Tour Advisor
Reservation and Travel Advisor
