by Svetlana Sicular | December 18, 2012 | Comments Off
“Data scientist is the sexiest job of the 21st century” (Harvard Business Review)
“Cybernetics is a whore of imperialism” (Stalin, 20th century)
I cannot quite catch an association between these two sentences. Maybe it’s in the transitions: from a whore — to the sexiest job, from East — to West, from socialism — to capitalism, from the past — to the present.
The most significant science, associated with the sexiest occupation of the 21st century, is math. This gets me thinking about what happens with mathematicians over time. In my high school for advanced math studies, we subscribed to a magazine for teenagers who were interested in physics and math. The name of the magazine was “The Quant.” And coincidentally, these were the teenagers some of whom later became the Wall Street quants. My schoolmates with advanced math degrees turned into actuaries, underwriters, hedge fund managers, entrepreneurs, quants, analytics experts, programmers and just mathematicians.
Here is the story of one of them. His dream was to be a math professor, and he was almost there. He got a job in the good East Coast university. But his wife, who worked on Wall Street, kept nagging him about great possibilities in the business world. He loved math, not money. Finally, he agreed to go to a job interview. The result was peculiar: my hero came back home super-excited because he met more advanced and accomplished mathematicians in the corporate world than in academia. The rest is history with a happy ending and impressive bonuses.
Last month, I met my classmate, who was the best in math among us, math kids. He dedicated his life to this science. I told him excitedly how sexy data science is, and consequently, about math with its sex appeal to data science. He did not understand despite his diligent attempts. I said I regret they did not teach us in college how math applies to various manifestations of life. He shrugged and said that it does not. I said there are new data paradigms that could use theoretical math in practice, for example, Banach spaces might expose intricacies of big data — that would be sexy. He told me that there are two maths: one is pure and high, and another one… Well, it also has a right to existence.
Bottom line. If we apply the math that is pure and out of this world to data, we might get unseen insights, not accessible otherwise. Some mathematicians can see with their mind’s eye spaces way more complex than just 3D — big data is not 3D either (it is viewed as 2D matrices at best right now). But there is a disconnect between two maths, the pure and the other, worse than a disconnect between the business and IT.
Follow Svetlana on Twitter @Sve_Sic
Category: data-scientist analytics big-data data information-everywhere innovation inquire-within mathematics skills
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