Graduated in Economics, with a master's and doctoral degree from the Federal University of Pará, focusing on Economic and Regional Development.Throughout my career, I have concentrated my efforts on analyzing socioeconomic data related to the bioeconomy in the Legal Amazon. I highlight my experience in data collection, structuring, and analysis, as well as my ability to construct indicators and conduct statistical and econometric analyses.At the Vale Technological Institute (ITV), I was responsible for structuring and analyzing socioeconomic data related to cocoa bioeconomy in the state of Pará. I developed indicators based on Machine Learning (ML) to categorize cocoa producers into homogeneous classes, enabling the identification of farmers' socioeconomic profiles.During my time at ITV, I utilized my programming skills for data collection, structuring, and analysis of public data. I created a database with social indicators using ML for the municipalities in mining territories, with a focus on municipalities surrounding the Carajás Railroad (EFC). This enabled the identification of the socioeconomic and environmental profiles of these locations.These efforts resulted in manuscripts, reports, and presentations grounded in scientific knowledge, supporting decision-making and the planning of sustainable development projects, in partnership with Vale.During my university years, I was selected for a foreign exchange program, where I continued my doctoral studies in England, focusing on climate change, deforestation in the Brazilian Amazon, and the role of public and private actions on issues arising from Land Use and Forest Changes.As a professional, I constantly seek to acquire skills to become an independent Data Scientist, capable of leading projects from data collection to the creation and implementation of ML models.At this stage of my career, I feel confident in my expertise and ability to build relevant solutions to improve project outcomes and establish myself as a standout professional.Analytical Tools: SQL, R, Python.Pipeline Tools: Github and SQLite3.Machine Learning: Classification, Regression, Clustering, and Time Series.