Darley Barreto
About Darley Barreto
Darley Barreto is a Senior Data Scientist with a strong background in machine learning and software development. He has worked at various organizations, including Avenue Code and Samsung Electronics, and holds a Master of Science in Computer Science from Universidade Estadual de Campinas.
Work at Avenue Code
Darley Barreto currently holds the position of Senior Data Scientist at Avenue Code. He has been with the company since 2023, working remotely for a duration of 10 months. In this role, he applies his expertise in data science to develop solutions that meet client needs.
Previous Experience in Data Science and Machine Learning
Prior to his current role, Darley Barreto worked as a Machine Learning Engineer at Pix Force for 5 months in 2023. He also served as a Machine Learning Engineer and Bayesian Software Engineer at PlantingSpace for 2 months in 2022. His experience includes working as a Data Scientist at NEX2ME, where he contributed to projects focused on enhancing chatbot intelligence and developing a proprietary platform for chatbots.
Education and Expertise
Darley Barreto earned a Master of Science in Computer Science from Universidade Estadual de Campinas, studying from 2018 to 2021. He also holds a Bachelor of Science in Computer Science from Federal University of Ceara, where he studied from 2014 to 2018. His educational background provides a strong foundation for his work in data science and machine learning.
Contributions to Projects
During his tenure at Insight Data Science Lab, Darley contributed to a project that involved creating a website with a feature for visualizing related terms and subjects in a graph format. At NEX2ME, he engaged in enhancing chatbot intelligence through natural language processing, which improved the understanding of user tasks.
Experience at Samsung Electronics
Darley worked as an AI Research Specialist at Samsung Electronics from 2021 to 2022 in Campinas, São Paulo, Brazil. During this time, he co-created a machine learning algorithm aimed at health improvement, designed for deployment to millions of users.