A Data Scientist is a Unicorn by Definition!

There are many definitions of data science and what a data scientist is, but no matter the source there’s general agreement that data scientists require three very important sets of skills:

  1. Math and Statistics. The end-to-end process for data science is deeply rooted in math and statistics. For example, creating understanding from often messy and disparate data requires statistical analysis. And, the techniques that data scientists apply, including all of machine learning, are largely based on mathematical formulas.
  2. Domain Expertise. Knowledge about a particular industry or department, including its business challenges and respective terminology, significantly increases the likelihood that a data scientist can find (and then solve) the right business problems.
  3. DevOps. Data scientists have highly specialized needs for data, storage, compute, and more during the R&D phase of their work. Later, they need to apply important DevOps steps to put their models into production.

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