Vinnicius Magalhães Stein Cezar Email & Phone Number

Porto, PT

United States

Allocated at Nasdaq. Working on on-premise migration to Azure Lakehouses with Azure Fabric

Brasília, Federal District, Brazil

• Worked for the client Bank of Brazil as consultant.
• Worked with Jupyter Notebooks in a Azure Databricks workspace;
• Agile methodologies (Scrum);
• As a Data Engineer, I builded a library with Python PySpark, Pandas and SQL, a Feature Store, aiming offer already processed, aggregated and manipulated data for consumption by data scientists and analysts;
• As a Data Scientist, I builded a model to predict Non-Performing Loan Ratio of clients based in time series events and their risks.

São Paulo, São Paulo, Brazil

Create and develop data pipelines and maintain machine learning models. I used clustering algorithms (K-Means) for classifications and matrix factorization (ALS) for recommendations in a recommendation system for retailer customers. Developed in an AWS environment, using PySpark for Big Data and Pandas for smaller amounts of data. SQL for data manipulation.

Barueri, São Paulo, Brazil

Used tools for ETL, data integration and maintenance/development of large-scale data pipelines in Talend, Apache NiFi and Python with PySpark for data migration from on-premise data to Azure Cloud and also offering data for API's. In agile methodology Scrum, I had direct contact the client, Scrum Master and Product Owner for a better understanding of.

São Paulo, São Paulo, Brazil

Create and develop Machine Learning models and analyze data for better insights. Always evaluating which is the best and most accurate model for making predictions or classifications, using evaluation metrics, depending on the algorithm (regression, classification or clustering). Python and frameworks / libraries like Pandas for data wrangling..

Santos, São Paulo, Brazil

Solve and pass on technical problems of the company's systems to analysts, such as bugs, dealing with debugging, troubleshooting and technical support for both internal employees and customers. The languages used: C # /.NET (on newer systems), Visual Basic (on older systems), ASP, Uniface, JAVA, Oracle and SQL Server database. Used SQL for data manipulation.