Skip to content
View rxavier's full-sized avatar
Block or Report

Block or report rxavier

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
rxavier/README.md

Hi! I'm Rafael Xavier

Summary

I am a data scientist holding a Masters degree in Economics. I have 7+ years of experience working with statistical and machine learning models, involving projects in public policy research as well as in consulting.

I work at Mercado Libre, Latin America's largest e-commerce site, as a Data Science Technical Leader. Prior to that I built and led a data science team at one of Uruguay's largest consulting firms.

Current projects

I enjoy building tooling for data scientists. My team built Embedding Encoder, a scikit-learn compatible transformer that leverages neural network embedding layers to process categorical variables, and I'm currently working on Poniard, a scikit-learn companion library that streamlines model evaluation.

Past projects

I built econuy, a data retrieval and processing library for Uruguayan economic statistics. I also built a Flask/Plotly Dash frontend hosted at econ.uy that's been online since mid-2020.

Pinned

  1. poniard poniard Public

    Streamline scikit-learn model comparison.

    Jupyter Notebook 145 9

  2. cpa-analytics/embedding-encoder cpa-analytics/embedding-encoder Public

    Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.

    Jupyter Notebook 40 7

  3. cpa-analytics/pyech cpa-analytics/pyech Public

    A Python package to analyze Uruguay's ECH survey.

    Python 1 1

  4. econuy econuy Public

    Wrangling Uruguayan economic data so you don't have to.

    Python 23