Felipe Barreto

Felipe Barreto

Data Scientist @ Conta Simples

About Felipe Barreto

Felipe Barreto is a Data Scientist at Conta Simples, where he has worked since 2020. He holds degrees in Civil Engineering and International Economics, and has expertise in cloud architectures and Big Data.

Work at Conta Simples

Felipe Barreto has been employed as a Data Scientist at Conta Simples since 2020. In this role, he applies his expertise in data science and engineering to support various projects within the company. His work involves analyzing large datasets and developing data-driven solutions to enhance business operations. Over the past four years, he has contributed to the company's objectives by leveraging his skills in cloud architectures and Big Data.

Education and Expertise

Felipe Barreto has an extensive educational background. He studied at Harvard Business School Online, focusing on business principles, and completed the CS50 course in Computer Science in 2019. He earned a Bachelor's degree in Civil Engineering from Ibmec, where he studied from 2015 to 2019. Additionally, he studied Finance at University Stars, achieving a Bachelor in International Economics and Management in 2017. His expertise includes cloud architectures, particularly with AWS, and Big Data, allowing him to work across data engineering and data science.

Background

Felipe Barreto began his professional journey in statistics and data driven by a desire to learn more about the field. Prior to his current role at Conta Simples, he worked as a Consultant at Ibmex for 11 months in Belo Horizonte, Minas Gerais, Brazil. This experience provided him with foundational knowledge and skills that he has since built upon in his data science career.

Achievements

Felipe Barreto has achieved notable educational milestones, including completing the CS50 course at Harvard Business School Online and obtaining a Bachelor's degree in Civil Engineering from Ibmec. He also earned a Bachelor in International Economics and Management from University Stars. His work spans various areas of data science and engineering, showcasing his ability to adapt and apply his knowledge effectively in different contexts.

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