This repository contains a collection of applied projects developed during my Master's degree in Data Science, focused on financial analytics, data engineering, and machine learning.
These projects represent the technical foundation that later evolved into my work on production-grade distributed AI systems (Tradu platform).
The repository includes:
- Financial indicators modeling
- Banking data processing
- SQL database design and querying
- Time series analysis
- Web scraping and data pipelines
- Geospatial and pricing analysis
- Applied machine learning for financial markets
All projects use public or anonymized datasets.
- Python (Pandas, NumPy, Scikit-learn)
- Jupyter / Colab
- SQL
- R
- Web scraping
- Data visualization
These projects were developed to:
- Build strong foundations in data engineering and analytics
- Apply statistical and ML techniques to real-world financial problems
- Design reproducible and structured data workflows
They served as the basis for later work on scalable AI platforms.
I am a Senior Data Scientist & Distributed Systems Engineer focused on building reliable, scalable, and observable AI platforms.
Creator of the Tradu distributed processing system.
📍 Argentina
🔗 LinkedIn: https://www.linkedin.com/in/leonardo-martinelli
Some original datasets and internal details are not included due to confidentiality constraints.