The main objective of this portfolio is to demonstrate my hard skills in solving business challenges through my knowledge of Data Science.

I am developing myself to execute all stages of developing a business solution using the concepts and tools of Data Science, from knowing the business issue to publishing the model on Clouds.

• Business Problem: Drugstore managers request sales forecasts for the next six weeks. Looking for the root cause, the data scientist spoke with the CFO to get more details about the request. The CFO explained the need to set the budget for carrying out the drugstores' repairs. Through sales forecasting, the CFO can determine the percentage of money each drugstore can use to make repairs.
  
• Solution Strategy: Through the application of the CRISP-DM methodology, it was followed 11 steps to determine the best machine learning model to forecast sales.
• Business Result: The solution aims to create a machine learning model that uses the drugstores' characteristics to forecast sales for the next 6 weeks. Information about the drugstore sales forecasting is shown on a Telegram Bot.
• Project: Sales Forecast Drugstores.

• Business Problem: Two businessmen, named Eduardo and Marcelo, wanted to start an e-commerce company called Star Jeans to sell men's jeans pants. The data scientist is responsible for determining the raw materials, types, colors, and best price to sell jeans pants.
• Solution Strategy: Using a script, the data was collected, cleaned up, and insert it into a database.
• Business Result: Based on the business criteria, a script is running to collect data from the website for a period. After that, the results will be analyze.
• Project: Star Jeans E-commerce.

• Business Problem: A data science project must have a reliable and repeatable process to ensure easy follow-up and understanding by all teams. It is essential to know all the steps in the CRISP-DM methodology.
• Solution Strategy: I conducted research on the subject, summarized the topics, and presented the information in an understandable way without losing scientific rigor.
• Business Result: I developed an online jupyter-book that describes in detail all the steps of the Crisp-DM Methodology
• Project: The Crisp-DM Methodology

• Business Problem: House Rocket's business model consists of purchasing and reselling properties through a digital platform. The data scientist is responsible for developing an online dashboard to help the CEO company overview properties available on House Rocket's portfolio and find the best business opportunities.
• Solution: I specified which properties are recommendable to purchase or not, considering region, median price, and season. I developed an online dashboard on the Heroku platform, making it easy for the CEO to perform data visualization, helping to choose the business decisions to get a high profit.
• Business Result: On the best option, the company must buy 11877 properties resulting in a US$1,420,125,681.90 profit. The profit with the business analysis of the real estate project will probably be 30% of invested value. The CEO can access an online dashboard
• Project: Exploratory Data Analysis

Professional with six years of experience working in a large company focused on information technology and services.

Solid knowledge in Understanding and solving problems, Oracle EBS and Oracle Database (creation of users, service accounts, and account changes), Prioritizing demands, and Continuous learning of new technologies.

• Master's degree in Rock Mechanics USP Polytechnic School.
• Major in Mathematics through University of Franca.
• Bachelor degree in Mining and Mining Engineering through Federal University of Alfenas.
• Bachelor degree in Science and Technology through Federal University of Alfenas