One of the most popular job roles in the world now, a data scientist is essentially someone who works with huge quantities of data possessed by organizations and analyzes it to extract useful insights that could offer valuable guidance to create useful business strategies. According to Investopedia, “the data scientist is often a storyteller presenting data insights to decision-makers in a way that is understandable and applicable to problem-solving.”
In the course of their data science career, data scientists work on a number of languages. In Europe, Python is effectively a universally accepted data science tool, as seen by over 90% of surveyed professionals saying they use it regularly. Among the other options, Jupyter Notebooks are used by 65%, and SQL is chosen by 60%.
Among the methods popular in the data science industry, the top three most popular choices are logistic regression, neural networks, and random forests, with upwards of 50% of respondents claiming to use each of these three. The variety among tool preferences clearly falls short of that seen in chosen data science methods.
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