The main objective of this data science personal project portfolio is to demonstrate my skills in solving business challenges through my knowledge and tools of Data Science

_{Data Scientist, taking a Bachelor's degree in Economics and in Software Engineer.}

Currently, trying to develop skills on the Machine Learning lifecycle, going from data collection and analysis to the model monitoring.

Data Engineering: SQL, SQL and NoSQL Databases, PySpark, Scala, Dbt, Airbyte.

Dev and Ops: Git, Docker, Python, Kubernetes, Terraform, Linux.

APIs: Rest, API Gateway, Flask, FastAPI, Django.

Workflow Orchestration: Airflow, ZenML, KubeFlow.

1. Store Sales Prediction

Building an end-to-end solution for a six weeks sales forecast of a pharmacy chain using Machine Learning. The predictions can be accessed by a bot on Telegram.

Skills: Machine Learning, Time Series, Heroku, API, Bot

2. Prioritizing Customers for Insurance Cross-Sell (Ongoing)

Predicting whether or not the customer would be interested in auto insurance so the sales can be optimized.

Skills: Machine Learning, Heroku, API, Streamlit

3. Cardiovascular Disease Detection (Ongoing)

Building a Machine Learning Model to detect cardiovascular disease in early stages leverage the diagnostic precision made by health professionals.

Skills: Machine Learning, Heroku, API, Streamlit

1. Education Dataset Analysis (Brazilian ENADE)

Analyzing data from a brazilian performance's valuation of students. The analysis is focused on the state of Bahia.

Skills: Data Visualization, Data Processing

2. Analysis of Election Data

Analyzing data from Vitoria da Conquista - Ba's 2020 elections. The focus is on the economic and the social profile of candidates.

Skills: Data Visualization, Data Processing

Spark	Python	Azure	FastAPI
Docker	Kubernetes	MLFlow	Flask