Reflections one year into working as a research software engineer

Abstract

Despite the obvious impact of software in research, we are still working out how to adequately acknowledge research software in academia. How do we provide rewarding career paths for those who want to write research software as academic output? The relatively new field of research software engineering can help address this. A research software engineer combines professional software expertise with an understanding of research. I have been working as a research software engineer in academia for the past year. In this talk, I will explain how this role fits into academia, what I do as a research software engineer, and summarise what I’ve learnt, and how I see, and hope, a career in research software engineering develops over time.

Slide available here

Resources

.large[

• greta
• usethis
• Nature article: Why science needs more research software engineers
• glue
• snapshot testing
• cli

]

Colophon

• Slides made using xaringan
• Extended with xaringanthemer
• Colours taken + modified from lorikeet theme from ochRe
• Header font is Josefin Sans
• Body text font is Montserrat
• Code font is Fira Mono

Bio

Dr. Nicholas Tierney (PhD. Statistics, BPsySci (Honours)) is a Research Software Engineer at Telethon Kids Institute in Perth, Western Australia. Previously he was a lecturer in Business Analytics and Statistics at Monash University, working with Professor Dianne Cook. His research aims to improve data analysis workflow, and make data analysis more accessible. Crucial to this work is producing high quality software to accompany each research idea. Mostly recently, Nick's work is focussing on exploring longitudinal data (brolgar), and improving how we share data alongside research ( ddd). Other work has focussed on exploring data with the R package visdat, and on creating analysis principles and tools to simplify working with, exploring, and modelling missing data with the package naniar. Nick has experience working with decision trees (treezy), optimisation (maxcovr), Bayesian Data Analysis, and MCMC diagnostics (mmcc.

Nick is a member of the rOpenSci collective, which works to make science open using R, has been the lead organiser for the rOpenSci ozunconf events from 2016-2018 (2016, 2017, 2018). Outside of research, Nick likes to hike, rockclimb, make coffee, bake sourdough, carve spoons, take photos, and explore new hobbies.

Github