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Just checked out your LI profile (fellow data science guy here) -- I think you basically need a bit more work experience or some github code to show yourself of
by binarysolo 14y ago
Just checked out your LI profile (fellow data science guy here) -- I think you basically need a bit more work experience or some github code to show yourself off. The big data guys like Google who have best practices, brand, and provide great onboarding should be your focus IMHO.
- tejaswiy 14y agoQuick question: What do you classify as work ex? I do mostly iOS programming, but I've been playing with Hadoop + the commoncrawl.org crawl data. Basically, I guess, what level of stats do you need to be comfortable with to call yourself a data scientist?
- deleted 14y ago[deleted]
- ahuibers 14y agoFollowing Gladwell's 10000 hour rule, I would say you could probably call yourself a data science after 1000+ hours experience working with datasets successfully. As far as the math goes you should be able to do regression analysis, you don't need to know tons of stats but you do need to know stats and probability essentials (first few classes at a good school) deeply. I like this Wikipedia entry on "mathematical maturity": http://en.wikipedia.org/wiki/Mathematical_maturity http://en.wikipedia.org/wiki/Mathematical_maturity; apart from writing proofs, it is very relevant.
- binarysolo 14y agoAt the end of the day, analytics is measured by effectiveness and appropriateness, not complexity. Simple regressions will do fine, but the "art" is to choose the right questions to ask. Typically if you're in a business setting that boils down to efficiency problems and maximizing time/money/happiness/etc. Dealing with these real-world problems = work exp.
- jboggan 14y agoThanks, I'm trying to find relevant ways to get that experience and working on some more sample code as well. What would you consider an "entry level" data science job?