I’m a data scientist with over 10 years of experience working with the full stack around R. I began as a researcher and transitioned to software development.

DOING AND ADVOCATING FOR REPRODUCIBLE OPEN SCIENCE

I started using the R stack around 2012, during the early stages of my PhD, and used it everywhere in my thesis from data-wrangling to advanced statistics and plots. By 2016 I was not only using the R ecosystem in my postdoc, but also helping others to "join the club".

ENGINEERING REPRODUCIBILITY AND OPENNES DIRECTLY INTO RESEARCH SYSTEMS

In 2017 I realized that I was passionate about reproducible and open science, and that I could not only advocate for it, but also I could "engineer" reproducibility and openness directly into the systems that researchers use. I left academia and worked at the Smithsonian Institution to transform a valuable but messy collection of R scripts into "fgeo," a "universe" of five R packages that I published and still maintain on CRAN.

To spread the love more widely, between 2018 and 2019 I joined The Carpentries as a data-science instructor and rOpenSci as an editor of peer-review software.

Also in 2019, I joined Theia Finance Labs to replicate the modernization project I had done before. Here I created "r2dii," another "universe" of four R packages which I published on CRAN and later delegated to co-authors.

Since 2022 I’ve been working on "tilt," my third "universe" of R packages and the first to have an interactive front-end built with R shiny.

TOOLS AND SKILLS

Over the years, I’ve mastered a range of free and open-source tools, including Linux, Docker, Git, R, and GitHub, and have tackled tasks spanning the entire data-science workflow: estimating effort, managing project boards, gathering, wrangling, and analyzing data, testing software, setting up CI/CD pipelines and cloud infrastructure, writing computational reports, building interactive applications, and teaching.

SERVICE

I regularly contribute to community projects to learn and share knowledge, such as my own data-science incubator on YouTube, the Ixpantia masterclass, and the rOpenSci Champions program.

DIRECTION

I plan to continue on this path — learning, sharing, and helping turn ideas into impactful data-science projects.