Isabela Assis Cardoso

Isabela Assis Cardoso has a diverse work experience in the field of software development and data analysis.

Starting in 2018, they worked as a Bolsista de Pesquisa Científica at the Universidade Federal de Minas Gerais, focusing on data analysis in the context of Nuclear Engineering. Isabela conducted detailed code analysis, optimized compilation processes, and utilized multiple programming languages such as Fortran and Python.

In 2021, Isabela joined the Centro de Inteligencia Territorial as an Estagiária em Ciência de Dados. Isabela'sresponsibilities included managing geospatial data, leading data migration projects, and conducting data analyses using cloud platforms such as AWS.

Continuing their career, Isabela worked as a Software Developer Node.js at ZENVIA, contributing to the development and maintenance of Node.js applications.

In 2022, they joined Foxbit as a Back-end Developer focusing on Ruby on Rails. Isabela'srole involved developing new features, optimizing existing code, and ensuring adherence to established development practices and architecture standards.

Most recently, Isabela started working as a Back End Developer at TotalPass Brasil in 2023.

With a range of experiences in software development, data analysis, and research, Isabela Assis Cardoso has demonstrated their proficiency in various programming languages and their ability to deliver high-quality results in diverse technical contexts.

Isabela Assis Cardoso pursued a Bachelor's degree in Physics from 2017 to 2023 at Universidade Federal de Minas Gerais. In addition to their formal education, they obtained various certifications from Digital Innovation One Inc., including "Acesso Remoto a Máquinas Linux," "Copiando Arquivos e Manipulando Processos," "Criando um Servidor Web com Linux," "Docker: Utilização Prática no Cenário de Microsserviços," "Gerenciamento de Discos Linux," "Gerenciando Usuários no Linux," "Infraestrutura como Código: Script de Criação de Estrutura de Usuários, Diretórios e Permissões," "Instalando o Linux," "Introdução ao Sistema Operacional Linux," "Manipulando Arquivos no Linux," "Servidor de Banco de Dados com Linux," "Servidores de Arquivos com Linux," "Tipos de Redes de Deep Learning," "Materiais Complementares: Introdução ao Machine Learning," "Algoritmos Genéticos," "Algoritmos de SVM (Support Vector Machine)," "Classificação de Problemas: Explorando Datasets," and "Introdução ao Machine Learning."