Due to my formation in mathematical engineering, I have strong knowledge in the foundations of machine learning. Also I’ve organized talks in the Tensorflow Usergroup Santiago, I’m also continously growing and taking courses in the subject.

At Noisegrasp, where I work currently, I’ve worked creating and training bayesian models for Marketing Mix Modelling using Docker, Google Cloud, PyTorch and Jupyter Notebooks.

Dedication, attention to detail, knowledge and a lot of curiosity are my biggest assets when developing a data science project.

What can I bring

• Analisys of tabular data
• Data Cleaning
• Feature Engineering
• Classification Models
• Regression Models
• Clustering
• Deployment

Technologies and libraries

• Python
• SQL
• scikit-learn
• matplotlib
• seaborn
• pandas
• polars
• PyTorch
• Docker
• Kubernetes
• Google Cloud
• FastAPI