One argument says that the growing sophistication of data science and machine learning platforms is decreasing the need for full-blown data scientists. That brings us to the topic of citizen data scientists, and whether they can actually replace their non-citizen brethren, or whether it’s just another case of trying to change the definitions of words in an attempt to thwart hostile reality.ĭata scientists sit at the confluence of several important skills But thankfully, that analyst broadside appears to have fallen by the wayside, and all in all, there appears to be somewhat broad agreement today by both employers and employees on what constitutes a data scientist. There was a push several years ago to dilute what the title mean, with SQL-loving data analysts trying to usurp the title to qualify for more jobs and move up the salary range. Different industries use data science differently, which impacts the specific skills that are needed. There are variations on this definition–check out Turing Award winner Jeffrey Ullman’s thoughtful take on what is a data scientist here–with some tweaks and additions to the specific skills that a data scientist is said to require.
Folks with this combination of skill are hard to find, which is why the average salary range for a data scientist nationally is $123,000 to $152,000, according to. You have undoubtedly seen the Venn diagram that shows the overlap of these three domains, with the rare data scientist sitting right in the middle. While definitions abound, the prototypical data scientist is usually said to possess skills in three areas: computer science, mathematics/statistics, and domain knowledge. This is true in some digital domains, but this linear form of thinking could get you into trouble in the field of data science and machine learning, particularly when trying to replace full-blown data scientists with so-called “citizen” data scientists.ĭata science is a complex field that requires practitioners to be proficient in multiple domains. Just as computer processing power increase over time, we’ve come to expect that technology will successfully automate more complicated tasks every year.
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