Title: I know that people say that &quot;interviewing is hard&quot; and I&#x27;ve read lots of articles that say that people generally don&#x27;t like doing long winded technical screens but it is the only way to judge whether or not a person is competent, etc.<p>What I want to know is why have other related areas of study such as Statistics, Economics, Actuarial Science and Operations Research been able to organize professional bodies that can determine competence. There are other professional bodies where they don&#x27;t give credentials but they organize a central location for candidates and organizations to come together and they provide a standardized format to determine competence.<p>I find this especially baffling now that &quot;data science&quot; has become a buzzword. Lots of &quot;data science&quot; techniques such as:<p>- Generalized Linear Modeling<p>- Gradient Boosted Machines<p>- Support Vector Machines<p>- Random Forrests<p>- The Simplex Algorithm<p>- Anything with the word Bayes or Markov in the title<p>were developed by Statisticians&#x2F;Mathematicians. Even though hospitals and insurance companies and the Fed and logistics companies are able to find statisticians&#x2F;operations researchers&#x2F; predictive modelers&#x2F; etc. with out problems why do tech companies such as AirBnB(https:&#x2F;&#x2F;www.quora.com&#x2F;How-does-Airbnb-hire-data-scientists) say they HAVE to give these multi-day long technical screens with multiple homework assignments?<p>What is it about applying the same techniques to tech that makes them special and some how harder to measure?
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