AI Trainer
Brand identification and bounding-box labeling, consistently meeting strict visual guidelines.
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I am a data professional with hands-on experience in data labeling, annotation, and quality control for AI training datasets, particularly in computer vision projects. My recent work as a Data Trainer involved achieving over 95% accuracy in brand identification and bounding-box labeling on large image datasets, while also refining annotation guidelines and reducing dataset noise by 20%. I am skilled in data validation, cleansing, and standardization, using tools like Python (Pandas, NumPy), SQL, Excel, and Power BI to ensure high data integrity. My background in Economics and Statistics, combined with my experience collaborating on remote teams, enables me to deliver reliable, high-quality training data that supports robust machine learning and analytics solutions.
Brand identification and bounding-box labeling, consistently meeting strict visual guidelines.
Certificate in Data Science, Data Science
Bachelor of Economics and Statistics, Economics and Statistics
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