About Me – Felipe Nunes Menegotto

Data Analyst & Developer

Felipe Menegotto

Physicist turned data analyst. I build end-to-end data projects with Python, SQL and Tableau – from extraction pipelines and data cleaning to predictive models and interactive dashboards, many of them deployed as live web apps. A BSc in Physics (UFRGS) and an MSc from the University of Lisbon give me a solid grounding in quantitative reasoning, statistics and the scientific method, and years of teaching taught me to explain results clearly to any audience. I have worked in four countries – Brazil, Portugal, Greece and Poland – in multicultural, multilingual teams.

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What I Do

Data Pipelines & Extraction

I collect and structure data that is not ready to use: web scraping, public APIs (Central Bank, TSE, DataJud, OpenAlex) and LLM-based extraction – such as turning ~3,000 match-report PDFs into a clean dataset with the Gemini API and Python.

Analytics & Dashboards

I clean, model and analyse data with pandas and SQL (BigQuery, PostgreSQL), and turn it into interactive dashboards in Tableau – using LOD expressions and inflation adjustment when the question requires precision.

Machine Learning

I train and validate predictive models (XGBoost, Gradient Boosting) with scikit-learn pipelines and deploy them as usable apps with Streamlit, FastAPI and Docker – reporting metrics like R² and MAE so users know how far to trust each prediction.

Web Apps & Research Tools

I build tools that run in the browser and solve real problems: computer vision with OpenCV.js and MediaPipe, automatic exam grading, and research tools for collecting YouTube data and managing scientific references.