Data Scientist, Ph.D. candidate in Theoretical Physics and Machine Learning student, I have experience in Data Analysis, Data Science, Artificial Intelligence and Machine Learning. I am a person with a self-taught profile, I always value teamwork and I seek to cooperate and help everyone in the best way possible, with great satisfaction in listening, learning and teaching. I have passion and great facility for dealing with numbers, mathematical modeling and programming.

Tools

• The programming language I master is Python. In addition, I had the opportunity to work with several programming languages ​​in my professional life, such as R, C/C++, Fortran, Matlab/Scilab, Wolfram Mathematica and PHP. Soon I will be starting my studies in Kotlin and Julia.
• SQL, with experience in MySQL, PostgreSQL and SQLite and also some experience with NoSQL in MongoDB.
• I have a background in Git, with personal repositories on GitHub and collaborative work on GitLab.
• Advanced knowledge of Scikit-Learn, Pandas and Numpy libraries.
• I always use TensorFlow for models that require Neural Networks.
• For statistical tests, I use Scipy and Statsmodels
• Advanced knowledge of Microsoft Office
• Experience in AWS for cloud services
• For Business Intelligence dashboards, I have experience using AWS QuickSight and Microsoft PowerBI
• I use DVC with GitFlow for data versioning and experiments
• Over the past year, I have been deepening my knowledge of the Hadoop ecosystem for using PySpark.
• Also, I have basic knowledge of Front-End and dealing with JavaScript, HTML5 or CSS codes are not an impediment for me.

Achievements

• IBM Professional Certification in Data Science. View credential
• Experience with scientific research, having published in international journals ​
• Participation in the development team of a credit monitoring model at RisKnow
• Kaggle notebook expert profile. Link to profile

Expertise

Python, Pandas, Scikit-Learn, Numpy, Scipy, StatsModels, TensorFlow, AWS QuickSight, AWS S3, AWS SageMaker, SQL, PostgreSQL, NoSQL, MongoDB, Git, Excel, Power BI, Business Intelligence, DVC, R, C, C++, Matlab

Projects

• PC Estate Price Predictor: An REST API written in Flask to predict Estate prices in Poços de Caldas, MG, Brazil
• Cov19: A Python package to make the non-linear parametric fitting of the Epidemiological Models SIRD applied to Covid-19
• Relating Neighborhoods from São Paulo to Rio de Janeiro using unsupervised machine learning
• xtlearn: Complementary classes to make easy the construction of sklearn pipelines
• regress: A python package to make polynomial regression with confidence interval
• Modelling the rental price for brazilian houses
• Credit card customer segmentation using unsupervised approaches
• Numerical sover for General Relativity prediction of Mercury precession
• Simulation of an Epidemic Spread