Building data science teams: The power of the technology stack | VentureBeat | Big Data | by Rodrigo Rivera, Rocket Internet
Summary
More often than not, Internet companies looking for a data scientist phrase their current job openings like this: “Expert knowledge of an analysis tool such as R, Matlab, or SAS and ability to write efficient code in at least one language (preferably Java, C++, Python, or Perl).” The problem here is that these are seven different skills for very different use cases. My experience has been that hiring a non-EU national and bringing him or her to continental Europe can take up to six months due to legal paperwork and relocation. As previously mentioned, hiring the right talent for data science is hard and takes time; you do not want to bring in somebody who fits on paper but does not adapt and later leaves. Nonetheless, it is important to discuss the type of potential projects that can fall into the area of responsibility of the team during the planning stage. Rodrigo Rivera is a Mexican German data entrepreneur and founder of Emplido, an analytics recruiting company acquired by Experteer Inc.
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