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TextI have solid experience in data labeling and AI training workflows, supported by a strong foundation in programming and applied mathematics. I’ve worked on projects involving facial recognition and automation systems, where I handled tasks such as annotating image and sensor datasets, validating classification outputs, and improving data consistency for AI models. My participation in challenges like the Kaggle “Disaster Tweets” competition also helped refine my skills in natural language understanding and label evaluation for NLP tasks. With a background in electronic engineering and a master’s in Innovation and Intellectual Property, I bring strong analytical thinking, proficiency in Python and C++, and a deep understanding of algorithms, logic, and statistics. These skills allow me to understand the technical context behind training data tasks and contribute with precision and efficiency. My experience also includes mentoring robotics teams and coordinating tech projects, where following detailed guidelines and delivering high-quality labeled data was key to success.
Build a machine learning model that predicts which Tweets are about real disasters and which one’s aren’t.
Bachelor's Degree, Electronic Engineering
Postgraduate Degree Professional Master’s Stricto Sensu, Intellectual Property And Technology Transfer For Innovation
Innovation and Technology Services Coordinator
Research Fellow
