I dislike when conversations about what data scientists should and shouldn't be doing default to being about education and skillset, rather than what their company hired them to do
Show this thread
-
There are a lot of reasons why this mindset is counterproductive, but the worst among them is how entitled it makes DS seem. When someone says "this isn't a good use of the time for someone with [X DEGREE]", people hear, "I think I am too smart to be doing something so menial"
Show this thread
It's definitely true that a lot of DS are asked to do things that aren't a good use of their time, but IMO that's more because our industry claims to value complicated, sophisticated-seeming solutions when its true north star is quick and decisive decision making.
-
-
Businesses hire DS because they believe (or hope) it will be a reliable way to get accurate information about the company, but this is a fundamentally practical need. If they could get the same quality of information from seances or palm readers, they might just do that instead
Show this thread -
Sometimes a cutting-edge or advanced technique really is the best tool for the job. Being able to identify those situations and use your hard-won knowledge is one of the most intellectually rewarding parts of DS work. But it's also fine if you rarely need to pull out the big guns
Show this thread -
Producing consistently valuable work, even if the way you do it seems too simple, will build trust with your stakeholders. Trust makes it easier to get space to solve bigger problems and maybe even find a way to flex and grow those more sophisticated skills
Show this thread
End of conversation
New conversation -
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.