Data Science as a Team Sport
I gave this talk at the 2019 RStudio::Conf in January in Austin, TX. The presentation was part of Track-1, org-thinking.
(Image Credit: Julia Silge)
How do you data science as a team sport? Oftentimes a data scientific initiative starts with just a single, lonesome data scientist. But when that germ of a team is successful and starts expanding, should the team be embedded in other disciplines or should it be centralized into its own function? Where should it live in the organizational structure? Should you focus on recruiting senior data scientists or is there a benefit to attracting junior talent as well? And in terms of capabilities, should you hold out for unicorns or hire several specialists to get all jobs done? Data scientists need to work on almost every aspect of a business, so how should a team composition set the data science discipline up for success? Great data scientists have career options and won’t abide bad managers for very long: if you want to retain them, you’ll need to care about their work, connect it to the business, and design a diverse, resilient, high-performing team.
Please note that this presentation was intended to be projected at rather high resolution, so the file is very large.
This presentation was video recorded. You can watch the videos at the following link: https://resources.rstudio.com/rstudio-conf-2019/data-science-as-a-team-sport
Being lucky enough to introduce people to something new is one of my favorite things 😄
Unconscious Bias (and Mirror-tocracy)
And since I'm neither a graphic nor a web designer, I can't take any credit for the design template—only for the contents of my talk. If you like the slides you can get the template here: https://www.goashape.com/shop/kaspian-keynote-presentation-template