Work with project to predict the score of potential customers for financial applications. For this we need to make a crawler to capture information, treat it in the best possible way, train and test algorithms for prediction. We use Python as the main tool and MongoDB as the database.

Main areas of study:- Machine Learning- Operational Research- Data Science

Full time position at State Health Department of Ceará. Working mainly in health applications with Data Science and Machine Learning in coordination with a development team, with many projects focusing in COVID-19 prevention and support to state administration.Technologies: Python (Flask, Jupyter, Scikit-learn), Docker, MongoDB, SQL, DataViz libraries (Plotly, seaborn, Folium), Airflow

The analysis of factors that alter the behavior of industrial equipment is one of the first steps to be able to carry out its automation by predicting its behavior using its current state. With the advent of 4.0 industry automation has become one of the important pillars for today's industry. This research aims to analyze and predict the behavior of vertical cement mills through Time Series using Deep Learning algorithms, based on the vertical mill of Companhia Industrial de Cimento APODI, located in Pecém-CE.

Was developed a system for meeting room management to Federal University of Ceará, using PHP, SQL database and Bootstrap.