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Clickworker
Appen
Mindrift
Image
Video
Text
Bounding Box
Segmentation
Classification
Entity (NER) Classification
Point/Key PointI have practical experience in AI training data and data labeling, contributing to projects that involved text annotation, data classification, content moderation, and quality assurance to support machine learning. I have worked on tasks such as sentiment analysis, intent tagging, named entity recognition (NER), and data validation, ensuring outputs were accurate, consistent, and aligned with strict annotation guidelines in different platfore such as Toloka,utest Apen etc. I am highly detail oriented and able to handle large volumes of data while maintaining speed and precision. What sets me apart is my strong ability to interpret complex guidelines, identify labeling errors, and improve dataset quality through careful review and feedback. I also have excellent communication and analytical skills, which helps me collaborate effectively with teams and maintain high annotation standards. With a background that supports structured thinking and reliability, I consistently deliver clean, well-labeled data that improves AI model performance and reduces retraining errors.
Drew bounding boxes around objects such as cars, people, road signs, and animals for computer vision training.
Classified messages into intents such as “order tracking,” “refund request,” “complaint,” “greeting,” and “product inquiry.” Helped improve chatbot response accuracy by properly labeling user queries.
Labeled customer reviews as positive, negative, or neutral to train sentiment analysis models. Tagged comments for emotions like anger, joy, sadness, or frustration.
Master of Science, Environmental Technology (Pollution Control)
Bachelor of Science, Microbiology
Toloka
AI Training Data / AI Evaluation Contributor
