Data Analyst | SQL | PostgreSQL | Python | Power BI | Machine Learning | Customer Analytics | Analytics Engineering
I'm a Data Analyst and PhD with over 15 years of experience transforming complex real-world datasets into actionable insights through SQL, Python, Power BI, statistics, and analytical modeling.
My scientific background has strengthened my analytical thinking, hypothesis-driven problem solving, and ability to design reproducible analytical workflows.
Today, I apply these skills to solve business problems in Business Intelligence, Analytics Engineering, Customer Analytics, and Machine Learning.
Applying scientific rigor and analytical thinking to solve business problems through modern data analytics.
- SQL
- PostgreSQL
- Power BI
- DAX
- Power Query (M)
- Analytics Engineering
- Customer Analytics
- Customer Segmentation
- Customer Lifetime Value (CLV)
- Star Schema
- Data Modeling
- Python
- Pandas
- Matplotlib
- R
- Statistics
- Machine Learning
- Scikit-learn
- XGBoost
- FastAPI
- REST APIs
- Docker
- Docker Compose
- Model Deployment
- Time Series Forecasting
- Predictive Modeling
- Feature Engineering
- Git
- GitHub
- DBeaver
- Excel
End-to-end Analytics Engineering and Business Intelligence project built with PostgreSQL, SQL, and Power BI, featuring a Star Schema data model, SQL semantic layer, business KPIs, and interactive executive dashboards.
🔗 Repository
https://github.com/felipeandrade91/Customer-Analytics-for-Brazilian-E-commerce
Customer Analytics project built with PostgreSQL, SQL, and Python, extending the previous analytical foundation through customer feature engineering, RFM segmentation, Historical Customer Lifetime Value (CLV) analysis, and business-oriented data visualization.
🔗 Repository
https://github.com/felipeandrade91/customer-segmentation-clv
An end-to-end Machine Learning project to predict customer churn using the IBM Telco Customer Churn dataset. The project demonstrates the complete data science workflow, including SQL data preparation, exploratory data analysis, feature engineering, predictive modeling, model evaluation and business interpretation.
https://github.com/felipeandrade91/customer-churn-prediction
Containerized REST API for customer churn prediction using FastAPI, Scikit-learn, Docker, and Docker Compose. The project demonstrates model deployment, input validation, automated testing, and containerized inference using the trained machine learning pipeline from the Customer Churn Prediction project.
🔗 Repository
https://github.com/felipeandrade91/customer-churn-api
An end-to-end machine learning project for retail sales forecasting using the Rossmann Store Sales dataset. The project covers exploratory time series analysis, temporal feature engineering, regression modeling, and model interpretation using Linear Regression, Random Forest, and XGBoost.
🔗 Repository
https://github.com/felipeandrade91/sales-forecasting-rossmann
A curated collection of my Business Intelligence, Analytics Engineering, Customer Analytics, Machine Learning, Time Series Forecasting, SQL, Python, and Power BI projects.
🔗 Repository
https://github.com/felipeandrade91/Data-Analytics-Portfolio
- PhD in Animal Biology (UNICAMP)
- Postdoctoral Researcher (USP)
- 28 peer-reviewed scientific publications
- Description of 13 new amphibian species
- 15+ years working with complex real-world datasets