About me

I am an accomplished data scientist with a strong background in Experimental and Theoretical Physics from Cambridge University, UK. I hold a PhD in String Theory from Queen Mary University of London and currently serve as an associate professor of physics at Universidad Adolfo Ibáñez in Chile. Proficient in the Wolfram Language and Python, I excel in numerical simulations and machine learning. Notably, I developed a successful Robo-Advisor using Chilean consumer data. I co-authored a chapter in a theoretical physics book published by Cambridge University Press (you can find the book here). My portfolio showcases diverse data science projects (you can find my Robo-Advisor project, along with several other of my projects, in my Portfolio), reflecting my passion for coding and innovation. It also includes my Lip reading project using Deep Neural Networks. I have experience with calculations that require GPUs. For example I adapted these to solve PDEs in an adaptive mesh refinement scenario (see my Wolfram community post here).

I hold certificates in both AWS and Azure Machine Learning Cloud expertise as well as expertise in the production and application of current Large Language Models.

Excited to contribute to cutting-edge data-driven solutions, I seek opportunities to apply my unique skill set in data science roles.

Quick Links

You can download my academic CV here or my Data-Science CV here.