Hi there! 👋

I'm an accomplished Data Scientist and Machine Learning Engineer who loves the challenge of taking a project from raw, messy data to a production-ready solution.

I specialize in building end-to-end pipelines on AWS SageMaker, with a deep background in Geospatial AI and Climate Tech. My goal is always the same: building models that don't just work in a notebook, but deliver real impact at scale.

Professional Journey

Data Scientist

2021 – 2025

Chloris Geospatial

  • Developed a production-grade ML pipeline on AWS to analyze 25 years of satellite imagery with 95% accuracy.
  • Scaled inference using a hybrid LightGBM and PyTorch CNN approach on SageMaker.
  • Built a Dask-based framework to handle petabytes of data ingestion.

Data Scientist

2020 – 2021

AmigoClimate

  • Created a Climate Extreme Index to forecast weather risks for the insurance sector.
  • Reduced simulated CO2 emissions by 10% through flight path optimization for the "ClimOP" project.

Postdoctoral Researcher

2019 – 2020

Sorbonne Université

  • Applied GAN-based inpainting to repair satellite datasets, improving completeness by 30%.
  • Researched tropical cloud systems using deep neural networks in TensorFlow.

Featured Projects

parcelas

Estimates the percentage of yearly sunny days across Chile by processing Landsat 8 & 9 satellite imagery.

View Project

ai-story

A full-stack web application that generates a book plot based on user-provided character names and a writer's name.

View Project

Open Source Contributions

Let's build something impactful.

I'm always open to discussing new opportunities, research collaborations, or just talking shop about Python and Physics.

Say Hello! ☕