08/12/2025 updated
100 % available
Data Analyst & Geospatial Specialist with Computer Science Background
Poços de Caldas, Brazil
Only remote
Bachelor's degree, Computer ScienceGeographic Information SystemsData AnalysisBusiness IntelligenceData CleansingProgramming ToolsEmergency ManagementPerformance ManagementEnvironmental ProtectionFinancial ModelingGeospatial AnalysisGitHubPython (Programming Language)Logistic RegressionMachine LearningNumPy
Data Analysis & Business Intelligence
Python programming with libraries like Pandas, NumPy, and Scikit-learn for data manipulation and analysis. Power BI, DAX, SQL, and advanced Excel/Google Sheets for financial modeling and business intelligence solutions.
Geospatial Analysis
QGIS expertise for geospatial data processing, thematic mapping, and burn scar analysis. Experience with environmental protection applications and disaster management assessment.
Machine Learning
Logistic regression, predictive modeling, and feature engineering skills. Development of machine learning models with high accuracy rates and implementation of real-time prediction functions.
Development Tools
Git, GitHub, Jupyter Notebook, and VS Code for version control and collaborative development environments.
Dashboard Creation
Design and implementation of interactive dashboards in Power BI with DAX measures to track KPIs and visualize business performance metrics.
Data Cleaning & Preparation
Techniques for data cleaning, transformation, and feature engineering to prepare datasets for analysis and machine learning applications.
Technical Documentation
Creation of technical maps in GeoPDF format and comprehensive documentation of data analysis processes and findings.
Python programming with libraries like Pandas, NumPy, and Scikit-learn for data manipulation and analysis. Power BI, DAX, SQL, and advanced Excel/Google Sheets for financial modeling and business intelligence solutions.
Geospatial Analysis
QGIS expertise for geospatial data processing, thematic mapping, and burn scar analysis. Experience with environmental protection applications and disaster management assessment.
Machine Learning
Logistic regression, predictive modeling, and feature engineering skills. Development of machine learning models with high accuracy rates and implementation of real-time prediction functions.
Development Tools
Git, GitHub, Jupyter Notebook, and VS Code for version control and collaborative development environments.
Dashboard Creation
Design and implementation of interactive dashboards in Power BI with DAX measures to track KPIs and visualize business performance metrics.
Data Cleaning & Preparation
Techniques for data cleaning, transformation, and feature engineering to prepare datasets for analysis and machine learning applications.
Technical Documentation
Creation of technical maps in GeoPDF format and comprehensive documentation of data analysis processes and findings.
Languages
EnglishFluentFrenchGoodPortugueseNative speakerSpanishFluent
Project history
Developed a Python-based machine learning model in Jupyter Notebook to predict passenger survival with ~81% accuracy. Performed data cleaning, feature engineering, and trained a Logistic Regression model using Scikit-learn. Created an interactive function for real-time survival probability estimation.
Conducted a geospatial analysis of a 369-hectare wildfire in the Uberaba River Basin EPA. Utilized QGIS to map burn scar, identify heat hotspots from satellite data, analyze probable ignition points, and produced a final technical map in GeoPDF format for disaster management assessment.
Designed and built an interactive dashboard in Power BI to analyze sales performance for a bicycle parts distributor. Created DAX measures to track KPIs such as Total Delivered, Lost, and Returned Orders. Visualized monthly sales trends by product line to identify top-performing products and fulfillment issues.