Edvaldo Melo
About Edvaldo Melo
Edvaldo Melo is a data scientist based in Rio de Janeiro, Brazil, known for developing predictive credit scoring models and enhancing customer retention strategies through predictive churn models. He has experience with AWS services and has worked at Zoox Smart Data since 2022, following a year as a data analyst at the same company.
Current Role at Zoox Smart Data
Edvaldo Melo currently serves as a Cientista de Dados at Zoox Smart Data, a position he has held since 2022. In this role, he focuses on developing predictive credit scoring models for both individuals and businesses. His work aims to enhance customer retention strategies through the implementation of predictive churn models. Edvaldo utilizes various AWS services, including S3, EC2, Redshift, and Quicksight, to facilitate data storage and analysis. He is also involved in creating machine learning applications using no-code platforms and designing dashboards for data visualization.
Previous Experience at Zoox Smart Data
Prior to his current role, Edvaldo Melo worked as an Analista de dados at Zoox Smart Data from 2021 to 2022. During this year, he contributed to the development of predictive models and automated processes to improve operational efficiency. His efforts supported the team by providing guidance and fostering a collaborative work environment. This experience laid the foundation for his current responsibilities in data science.
Education and Expertise
Edvaldo Melo studied at Universidade Federal da Paraíba, where he earned a Mestrado em Informática from 2019 to 2021. His academic background also includes a Bacharelado em Matemática Computacional, which he completed from 2013 to 2018. His education has equipped him with a strong foundation in computational systems and modeling, which he applies in his data science work.
Technical Skills and Tools
Edvaldo Melo possesses a range of technical skills relevant to data science. He is proficient in using AWS services such as S3, EC2, Redshift, and Quicksight for data management and analysis. Additionally, he has experience in designing and developing dashboards using Tableau and Amazon Quicksight. His ability to create machine learning applications through no-code platforms further demonstrates his versatility in data-driven projects.