Experienced Data Scientist with a solid foundation in Electronic Engineering and Quantitative Finance, bringing over 20 years of programming and data analysis expertise. I transitioned into Data Science in 2023, achieving 1st place at the 6th Hackday of the DS Community with a machine learning-based pricing prediction system. My skill set spans predictive modeling for sales forecasting, customer segmentation, and the development of interactive dashboards using Streamlit.Using Python, SQL, Scikit-Learn, and advanced techniques like Random Forest, K-Means, and XGBoost, I solve business challenges with data-driven insights. A recent project involved customer classification, which drove a 181% increase in campaign revenue, with the code available on GitHub.I am the author of three research studies (see Publications section):1. Forecasting Brazilian Interest Rates with Dynamic Models Using Momentum and Neural Networks – Presented as a dissertation for the MSc in Quantitative Finance from University College Dublin in 2010, this work explored predictive modeling with neural networks and momentum for forecasting interest rate fluctuations.2. The Judiciary Budget of the Court of Justice of Rio de Janeiro (TJRJ) – A thesis for my Law degree from Universidade Federal Fluminense, analyzing financial flows from 2016 to 2022, with a focus on the TJRJ budget.3. Economic Analysis of Tax Burden Distribution in the Digital Economy – Published by Universidade Federal Fluminense in 2020, this study examines tax burden distribution within digital contexts and offers reflections on fiscal impact in the digital economy.I am a collaborative, results-oriented professional, always seeking new opportunities to leverage Data Science to generate value. Let’s connect to explore challenging projects where I can contribute with data insights that drive strategic decision-making.Technical Skills:Analytical Tools: Python, SQLDevelopment Tools: GitHub, SQLite, MySQL, MS-AccessMachine Learning Techniques: Classification, regression, clustering (including Linear Regression, XGBoost, CatBoost, LightGBM, Decision Trees, Random Forest, Voting Regressor)Languages: Python, C, Visual Basic, VBA, PHP, WordPress Plugin DevelopmentProject Portfolio: http://menezes.mendonca.nom.brContact: manoelmendonca@hotmail.com