Chris U. Carmona

Chris U. Carmona

Doctoral Researcher in Statistical Machine Learning

Department of Statistics, University of Oxford

I am Chris Carmona, a doctoral researcher in Statistical Machine Learning at the University of Oxford, advised by Prof. Geoff Nicholls.

Recently, I have been working on two main lines of research: 1) Semi-Modular Inference (SMI), a Bayesian method to learn from multiple sources of information under difficult conditions, such as model misspecification and copious missing data; and 2) Probabilistic models for dynamic relational data, with applications to large datasets of financial transactions.

I hold a master degree in Applied Statistics from UC Berkeley, and have also been lecturer at the National University of Mexico in subjects on Statistical Learning and Actuarial Modelling.

Besides my academic track, I have collaborated in public and private institutions. I’m currently a Machine Learning Scientist at Amazon Web Services. I’ve held several positions at the Central Bank of Mexico, including Senior Financial Researcher, and Head of the Financial Risk Office within the Directorate of Risk Management. I’ve also participated in consultancy projects to estimate the official poverty indicators in Mexico for CONEVAL.


  • Probabilistic Modelling
  • Bayesian Inferential Methods
  • Computational Statistics
  • Machine Learning


  • DPhil in Statistics, 2020

    University of Oxford

  • MA in Statistics, 2014

    University of California, Berkeley

  • BSc in Actuarial Sciences, 2009

    National University of Mexico (UNAM)


Professional experience


Machine Learning Scientist Intern

Amazon Web Services

Sep 2020 – Present Berlin, Germany

Data Science Researcher


Aug 2019 – Aug 2020 London, United Kingdom
  • Developed methods for Anomaly Detection in Dynamic Relational Data (Financial Networks).

Senior Financial Researcher

Central Bank of Mexico

Jan 2016 – Sep 2016 Mexico City, Mexico
  • Financial risk management for the assets in Mexico’s international reserve.
  • Portfolio optimization using a number of methods for asset allocation.
  • Created in-house computational tools for financial risk modelling.
  • Actuarial analysis of the central bank’s private pension plan.