Happening in this #rstudioconf block (1:23, Imperial ballroom): "UnicoRns are real"!
I'll show salary data for data scientists across the US, and how R-centric job descriptions can be written to align. Details in thread.
https://unicorns-are-real.netlify.com/
https://github.com/tgerke/unicoRns-are-real …
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With the help of a fantastic HR compensation consultant, I wrote R-centric job descriptions (slide 21) that map to the salaries shown on slides 22-23.pic.twitter.com/IRlLJT06uh
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Goals: empower unicoRns to capture the salary they deserve, and empower data science hiring managers to recruit and appropriately compensate the unicoRns they need.
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Thanks, these slides are really interesting. Something I wonder a lot, is it worth investing in self learning to become a unicoRn versus being flexible about language & learning wider range of tools (eg python). Investment in former means you can be far more versatile & nimble.
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... latter means you open opportunities in teams using other tools (sometimes a single lang choice like python is adopted in some places), but means relearning basics. I know that's not what your talk is about, but it connects to the unicoRn idea. Curious to hear any views!
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