Renato Aranha
About Renato Aranha
Renato Aranha is a Data Scientist with a strong background in business and soft skills, enabling effective collaboration in diverse teams. He has extensive experience in data science and advanced analytics, currently conducting machine learning research at IBM Research.
Current Role as Data Scientist
Renato Aranha has been employed as a Data Scientist since 2019. In this role, he applies his expertise in data science and advanced analytics to various projects. His work involves leveraging data to derive insights and support decision-making processes. Aranha's strong business and soft skills enhance his ability to collaborate effectively within interdisciplinary teams.
Work at IBM Research
Aranha conducts machine learning research at IBM Research, focusing on applications within the natural resource industry. He has been a PhD Research Intern at IBM since 2020. His research contributes to the development of innovative solutions that utilize machine learning techniques to address industry-specific challenges.
Education and Expertise
Renato Aranha holds a Bachelor of Science in Physics from Universidade Federal do Rio de Janeiro, completed in 2009. He furthered his education at Fundação Getulio Vargas, where he earned a Master of Science in Applied Mathematics in 2019. He is currently pursuing a PhD in Artificial Intelligence at Universidade Federal do Rio de Janeiro, expected to be completed in 2023.
Previous Work Experience
Aranha has a diverse work history in data analytics and business intelligence. He served as a Business Intelligence Trainee from 2010 to 2011, followed by roles as a CRM & Data Mining Analyst and Coordinator from 2011 to 2013. He also worked as an Advanced Analytics Coordinator from 2015 to 2017 and as a Research Assistant from 2017 to 2019. His experiences have equipped him with a comprehensive understanding of data-driven decision-making.
Passion for Data Science
Renato Aranha's passion for data science and advanced analytics is evident in his successful completion of various projects in the field. His commitment to leveraging data for insights reflects his dedication to continuous learning and application of analytical techniques in real-world scenarios.