π Data Scientist | Python & Machine Learning
- Machine Learning & Quantitative Analysis: Developing result-oriented predictive models (XGBoost, Scikit-Learn, Pandas, NumPy).
- MLOps & Automation: Implementing autonomous architectures for the model lifecycle (GitHub Actions).
- Data Storytelling: Creating interactive interfaces to democratize access to complex data (Streamlit, Plotly, SQLAlchemy).
- Languages: Python, SQL.
ML Platform for Quantitative Analysis (S&P 500) I developed an autonomous MLOps architecture that processes years of Big Data without manual intervention. The system uses XGBoost and real-time mathematical validation to predict directional probabilities, eliminating emotional bias in investment decision-making.
π¬ "The ability to communicate data is as important as the ability to analyze it."