Programming Languages and Database
- Python for data analysis.
- SQL for data extraction.
- Databases: SQL Server, MySQL, PostgreSQL, InfluxDB
My name is Matheus Andrade. I have a degree in Mechanical Engineering and a master's degree in Mechatronics.
I currently work as a researcher on topics related to Industry 4.0 and also as an application developer in the field of industrial automation.
I am developing personal projects on Data Science to gain experience in solving business problems and improve my abilities with the tools that a data scientist uses on a daily basis.
I am looking for an opportunity to work professionally as a Data Scientist to improve the company decision making by building solutions using data.
I have experience in Object Oriented Programming, Computer Vision, Multi Agent Systems, Evolutionary Computation, Database Administration and Machine Learning. I've already worked with Python, Matlab, SQL, HTML, CSS and JavaScript.
Customers Clustering for High Value Customers Identification abd Loyalty Program Creation.
Regression for Oil Production Prediction for Several Wells.
Customers Classification to Rank Database According to Purchasing Propensity.
Regression for Drugstores Sales Prediction.
Computer Vision for Liquid Column Measurement in Real Time.
Insights for the Real State Market to Help the CEO to Find the Best Homes to Buy and Sell.
Insights for the Real State Market to Assist in the Observationb and Analysis of House Prices.
1 year of experience developing applications for the industrial automation sector.
UFBA (Federal University of Bahia), PPGM (Graduate Program in Mechatronics)
Development of a computer vision application for measurement of a column of liquid and development of a digital twin aimed at improving performance using machine learning, genetic algorithms and multi-agent systems as a tool for production data analysis in the master's degree.
UNIFACS (Universidade Salvador)
The business team asked the data scientists to select the most valuable customers for the company Recency, frequency and monetary aspects were considered by the business team as the main characterists to evaluate the customers in clusters.
Production prediction is one of the core problems in a company. The provided dataset is a set of nearby wells located in the United States and their 12 months cumulative production. The company data scientist needs to build a model from scratch to predict production.
An insurance company wants to start selling vehicle insurance to the customers that already have health insurance. They believe that one of the ways to reach as many customers as possible with the least amount of calls is to make a machine learning model that sorts the list of customers to maximize the amount of contracted services.
The CEO from Rossmann wants to renovate all stores and asked wants to know what the income of all the stores will be in the next 6 weeks. A regression model would be of great help.
Computer vision system to measure the essential oil produced by steam distillation in real time communicating with supervisory applications using Modbus TCP.
The House Rocket is a real state company. The data scientist from House Rocket should help the CEO answering two questions and creating two tool to help understanding the dataset.
Real estate insights project, using a dataset from Airbnb, in New York, to help the company's CEO to evaluate the behavior of the prices of properties available in the city.