Wrong but useful. Working @Twitter, tweeting about data science and people management.
"Wait, it's all her views?" 
"Always has been"
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I'm exaggerating a little, but many seasoned DS have probably had a similar feeling or experience. Depending on your mindset, it can be an ego hit (or at least bit of a bummer) to realize what you're doing is primarily a commercial activity and not capital S science
But DS never was science proper. It's a hybrid of at the Venn diagram intersection of hacking skills, math & statistics knowledge, and substantive expertise.
The business environment of the late aughts and early 2010's suddenly meant that this was a relevant combo of skills, and the emphasis on people having all three skills meant there needed to be a name for such people. Thus the sexiest job title of the 21st century was born.
But DS's hype has worn off. Practitioners are disillusioned, and in frustration, they decide to go work as SWEs or ML engineers or PMs because it seems more straightforward to stick to just one circle on the venn diagram.
But you know what? DS is starting to emerge from its awkward adolescence. It's developing its own identity and carving out its own role in the modern business. And @IanWhitestone has wonderfully distilled its essence in his post
DS try to get buy in by contributing in the same way that SWEs, MLEs and PMs contribute, but DS is its own craft. DS can be similar to those roles, but it's best when it focuses on its own raw materials and tools and uses them to create value that no other functional role can
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