Data Science undergraduate at ICMC-USP focusing on AI Engineering, Multi-Agent Systems, and applied Machine Learning.
I build end-to-end data pipelines, predictive models, and autonomous LLM workflows designed to turn unstructured information and relational databases into structured, actionable insights.
- Multi-Agent Architectures & LLM Tooling: Designing agentic workflows for automated data analysis, Text-to-SQL, and contextual insight generation.
- Applied Machine Learning: Feature extraction, tabular modeling (XGBoost, Random Forest), and rigorous statistical evaluation.
- Data Pipelines & Engineering: SQL database modeling, reproducible data processing pipelines, and scientific computing.
- Languages: Python, SQL, C/C++
- ML & Data Science: Pandas, NumPy, Scikit-learn, XGBoost, PyTorch, LangGraph, SciPy
- Environment & Tools: Linux/WSL2, Git, Docker, LaTeX
- LinkedIn: linkedin.com/in/luizgcorreiadosantos
- Email: [email protected]