rstudio::conf(2022)

Data suggests that less than 3% of data scientists are women of color. My journey and that of many other women who fall at the intersection of being underrepresented in this field is one that is often filled with pitfalls and curves that can result in continued exclusion in these spaces. My journey as a historically excluded double minority in STEM is one of triumph, but not without the community educational tools, online platforms and genuinely inclusive members of the R Studio and open science communities. My work explores how we can build on these tools and further propel the use of open science as a tool for equity and diversity in STEM, now more than ever.

The Carpentries is a global community of volunteers who collaboratively develop and deliver lessons to build capacity in data and coding skills to researchers worldwide. In the recent redesign of our lesson infrastructure (serving >100 lessons, used daily by >5K learners), we replaced embedded Jekyll templates with a workbench of modular and accessible packages using R and Pandoc. By leveraging renv and knitr for R-based lessons, we provide a seamless and collaborative lesson development experience that maximizes reproducibility and minimizes frustration so authors can focus on the contents, not the tooling. We demonstrate how anyone can use our infrastructure to build customised and accessible sites for their own lessons or tutorials.

Talk materials are available at https://github.com/zkamvar/rstudio-conf-2022.

In community conversations at the Data Science Hangout, we’ve talked about misalignment between what recruiters are looking for and who is actually a great fit for a role. At one point, people started sharing their own degrees in the chat: sociology, political science, finance, psychology, no degree, etc.

What makes us good at our jobs is so much more than the degree that we have.

I’m not a data scientist. When I think about my own role though, much of my intuition comes from growing up in a restaurant and watching my mom create a community among customers.

This talk will share a few community building tips to get you started and perhaps a little inspiration to consider the other skills that qualify you for what you want to do.

In this presentation, I will share my experiences at the intersection of the R and Kaggle communities. As Kaggle's first Notebooks Grandmaster, I will talk about how R users can contribute and thrive in an increasingly Python dominated community. A strong focus will be on the art of building insightful and engaging Kaggle notebooks and exploratory data analyses in general. I will share my lessons from running a weekly series aimed at promoting underrated Kaggle notebooks and their authors. And I will talk about organising a Kaggle insights competition aimed at exploring this dataset of 100 episodes, and what it taught me about community dynamics, different approaches to exploratory challenges, and the creativity of the participants.