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Senior Data Scientist working on process and pricing optimization, causal inference, and physics-informed machine learning.
Machine Learning project focusing on predicting the volume of hectoliters to be sold for different products over two horizon periods, and then optimizing the net revenue while minimizing the investment budget (discounts).
Predict the frequency of vehicle accidents over time. 
My master’s thesis: a Python library that solves partial differential equations with Physics-Informed Neural Networks, using a Deep Q-Network agent to learn where to place collocation points. Published on PyPI as pinnrl.