Decision Scientists build decision support tools to enable decision makers to make decisions, or take action, under uncertainty with a data-centric bias. Traditional analytics falls under this domain. Often decision makers like linear solutions that provide simple, explainable, socializable decision making frameworks. That is, they are looking for a rationale. Data Scientists build machines to make decisions about large-scale complex dynamical processes that are typically too fast (velocity, veracity, volume, etc.) for a human operator/manager. They typically don’t concern themselves with whether the algorithm is explainable or socializable, but are more concerned with whether it is functional, reliable, accurate, and robust. … Decision Scientist
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24 Friday Apr 2015
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