Rafael D.
About Rafael D.
Rafael D. serves as the Data Science Lead at C6 Bank, where he has worked since 2022. He has a strong background in data science and credit risk modeling, with previous roles at Neon and Banco Pan.
Work at C6 Bank
Rafael D. has been serving as the Data Science Lead at C6 Bank since 2022. In this role, he has led the development of the first generation of auto loans, employing causal inference methods to create pro pension scores for pricing. He has also implemented automatic credit policy methods, which improved the efficiency of credit model creation using Google Cloud Platform (GCP) and BigQuery.
Previous Experience in Data Science
Before joining C6 Bank, Rafael D. worked at Neon in various capacities. He served as a Senior Data Scientist focusing on Modeling and Credit Risk for six months in 2021. He also held the position of Data Scientist in the same area for one year from 2020 to 2021. Additionally, he was a Data Science Tech Lead at Neon for 11 months in 2022, where he led a team that developed the first generation of models for managing the FIDC Neon and the second generation of credit card models.
Early Career in Credit Risk Analysis
Rafael D. began his career as a Junior Credit Risk Analyst at Banco Pan, where he worked for eight months in 2019. He also gained experience as an intern at Itaú Unibanco from 2018 to 2019. His early roles provided him with foundational knowledge in credit risk analysis, which he has built upon in his subsequent positions.
Education and Expertise
Rafael D. holds a Bachelor's degree in Ciências Econômicas from Universidade Estadual de Campinas, where he studied from 2015 to 2019. He also completed a Técnico em Mecânica at Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP) from 2011 to 2014. His educational background supports his expertise in data science and economic analysis.
Technical Skills and Technologies
Rafael D. is proficient in various technologies essential for data science and machine learning. He has utilized Python, SQL, AWS, Spark, Trino, Presto, Xgboost, and Lightgbm in his roles. His technical skills enable him to lead machine learning engineering teams effectively and implement advanced data-driven solutions.