I hold a Bachelor’s degree in Computer Science with experience in data science, data engineering, and back-end development. I have worked in junior companies, startups, as a freelancer, in consulting, in retail, in technology companies, and I currently work at the Electoral Justice.
In the academic field, I spent one year working on predictive system modeling and climate classifiers using data from the National Institute of Meteorology, predicting gasoline prices in the state of Amapá. Later, I was a PIC-PROBIC UNIFAP scientific initiation fellow, where my research focused on Music Information Retrieval (MIR), including classifiers of Amazonian musical genres and musical instrument classification.
I have experience in building APIs, automation with RPA, exploratory data analysis and modeling of machine learning algorithms, multi-objective mathematical optimization, and creating APIs to serve machine learning models. I also work with data processing on AWS, from ingestion and ETL to queries in Athena.
Currently, I am deepening my knowledge and practice in RAG (Retrieval-Augmented Generation) and LLMs (Large Language Models), aiming to integrate these solutions into real-world scenarios to optimize processes, enhance decision-making, and expand the possibilities of intelligent automation.
This background, combined with daily collaboration in multidisciplinary teams, has allowed me to develop strong communication, teamwork, and the ability to understand how each delivery can positively impact the business, always envisioning ways to improve solutions and solve everyday challenges.
