Danilo Carlotti
About Danilo Carlotti
Danilo Carlotti is a data scientist and consultant based in São Paulo, Brazil, with extensive academic and professional experience in data science, law, and economics. He has held various roles in notable organizations and has completed multiple degrees at the Universidade de São Paulo.
Work at BairesDev
Danilo Carlotti has been employed as a Data Scientist at BairesDev since 2023. His role involves leveraging data analysis and machine learning techniques to drive business insights and support decision-making processes. BairesDev is known for providing technology solutions and services, and Carlotti contributes to the company's data-driven initiatives.
Education and Expertise
Danilo Carlotti holds a diverse educational background. He studied at USP - Universidade de São Paulo, where he completed a Bachelor's degree in Law and a Master's degree in Philosophy and General Theory of Law. He also achieved a Doctorate in Law from the same institution. Additionally, he pursued studies in Computer Science, completing a Postdoctoral research position from 2020 to 2023. He further enhanced his expertise in Economics with a Postdoctoral research at Insper Instituto de Ensino e Pesquisa.
Background
Danilo Carlotti has a multifaceted career that spans various roles in data science and academia. He began his professional journey in law and philosophy before transitioning to data science. He has worked in several organizations, including Instituto Brasiliense de Direito Público as a Professor and Lexter.ai as a Data Scientist. His experience also includes leadership roles, such as Head of Data Science at Educbank and Coordinator at will bank.
Achievements
Throughout his career, Danilo Carlotti has made significant contributions to the field of data science. He has held multiple positions that leverage his expertise in data analysis, including his current roles at THS as a Data Science Specialist and as a Principal Cofounder at GOVY. His involvement in various organizations showcases his ability to apply data science principles across different sectors.