I'm an analytical professional who can effectively work in diverse teams. A data-driven individual who recognizes the value that research, documentation of processes and teamwork can bring to innovation.
Data Science & Analytics Tools: SQL • Python • Power BI • Pandas • Numpy • Scikit-learn • SAP Hana
Data Engineering Tools: Cloud (Databricks) • ETL Development • PySpark • Git • Control-M • Data discovery and Relational Modeling
Machine Learning, Statistical & Descriptive Analysis, Storytelling, BI Development
I'm currently a Data Analyst at Sicredi, one of the largest financial cooperative institutions from Brazil, performing in data projects within Internal Auditing.
Below, you can check my main personal projects within the universe of Data Science, Engineering and Analytics. Click on Learn More to see more details!
This is a MLOps project focused on building a full solution to the challenge of creating a model to predict if a customer, in a bank, will execute a specific transaction in the future. Hence, it is a binary classification problem.
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This project aims to build a Web App that provides the prediction of house prices in New York along with a AI report generator that uses a LLM and RAG system to give the user more insights on the chosen house features.
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This project focuses on building a system that provides, for both patient and doctors, an assistant to interpret the symptoms that a patient has, providing a first orientation on the possible disease and the respective treatment. An LLM + RAG system was developed and implemented to serve this purpose.
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This project focuses on building a model to be applied to Home Credit Default machine learning challenge to predict the client's repayment abilities, providing the potential default occurrence of a client. Data modeling using dbt core was also used.
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ML project focused on developing a model and ML App that classifies a financial transaction as fraudulent or not. This kind of data-driven classification is key in order to guarantee the security in financial institutions.
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This is a hypothesis testing study focused on checking the implications of changing a feature within a game related to user retention and number of rounds played.
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This is a machine learning project focused on providing a satisfactory approximation of the time taken to make a food delivery, in minutes, for a food delivery company. Having a prediction of the time it will take for your delivery to reach your location after it leaves the restaurant is a very important feature to have regarding customer service.
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This is a data engineering project that showcases the use of Airbyte, dbt Cloud and Postgres in the creation of a cloud database to store liquor sales data in the state of Iowa, USA.
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This is a Data Analysis and Engineering project developed in order to solve the challenge of creating a serverless Data Warehouse using Google BigQuery connecting to the sales history data of Liquor in the state of Iowa, USA, using an API to extract the Data, PySpark to process the Data and Power BI to analyze it to provide business insights.
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