As we announced last year, RStudio’s summer intern program will run for a third time in 2020, and applications are now open. Five people will work with an RStudio mentor full-time for 10 weeks starting in May 2020. Everyone is welcome to apply: you do not need to be a a full-time student to be eligible for an internship.
The compensation rate for these positions is $25/hr, assuming 40 hours each week; applicants must be residents of, and able to accept employment in, the United States. Since RStudio is a geographically distributed team, you can be based anywhere in the country: unless you live in Boston or Seattle, you will be working 100% remotely, though you will meet with your mentor regularly online.
How to Apply
The closing date for applications is midnight on Friday, March 6 AOE (Anywhere on Earth), and we will interview and make offers as quickly as possible thereafter.
This year’s internships will be divided between our open source and education teams, and the projects will be selected from:
Create resources for people working with spreadsheets in R. Develop content that does for spreadsheets what sites like db.rstudio.com and environments.rstudio.com do for databases and reproducible environments, respectively. Primary tasks will include writing, synthesis, comparison, exposition, and exampling. This project is not explicitly about package development, although the work could easily lead to pull requests to spreadsheet reading/writing packages. Candidates should show evidence of general R experience, basic competence with Git/GitHub, previous use of R Markdown, and ability to write clearly about code. Supervisors: Jenny Bryan and Mine Çetinkaya-Rundel.
Build interactive learnr tutorials for tidymodels based on our existing introductory tidymodels workshop materials. Candidates should show evidence of having used R for data analysis and/or statistical modeling as well as basic competence with Git and GitHub; experience using the learnr package is a plus. Supervisor: Alison Hill.
Build interactive learnr tutorials for Python using reticulate. These would mirror the content of our existing tidyverse primers. Candidates should be comfortable using R or Python for data science and have basic competence with Git and GitHub; experience using the learnr package is a plus. Supervisors: Alison Hill and Greg Wilson.
Tidymodels package support. This intern will work on the support and development of modeling packages, primarily broom, which provides a large number of methods to turn models into tidy data frames. The work will include internal refactoring, revisit the testing strategy, and further develop the
augmentmethod. Candidates should understand R packages, S3 methods, and unit testing, and be comfortable using Git and GitHub. Supervisor: Max Kuhn.
Tree and rule-based models. The Cubist and C50 packages contain large amounts of C code to train ensemble models. This intern will improve their sustainability and add new features such as variable importance, efficiency, and cost-sensitive models. Candidates should understand R packages work, have solid C skills and some experience with modeling, and be comfortable using Git and GitHub. Supervisor: Max Kuhn.