Quanto vale um cientista de dados?

No início deste ano, o professor e CEO de Economia do Google Hal Varian disse que a estatística estará em alta nos próximos dez anos: "People think I’m joking, but who would’ve guessed that computer engineers would’ve been the sexy job of the 1990s?".

Entretanto, ao ler a entrevista que Hal concedera a The MacKinsey Quartely conclui-se que o professor chama de "estatístico" o profissional com capacidade para extrair informações de uma grande base de dados e apresentá-las de modo atraente ao usuário não especializado.

"We’re in the middle of a period that I refer to as a period of “combinatorial innovation.” So if you look historically, you’ll find periods in history where there would be the availability of a different component parts that innovators could combine or recombine to create new inventions. In the 1800s, it was interchangeable parts. In 1920, it was electronics. In the 1970s, it was integrated circuits.

The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades, not only at the professional level but even at the educational level for elementary school kids, for high school kids, for college kids. Because now we really do have essentially free and ubiquitous data. So the complimentary scarce factor is the ability to understand that data and extract value from it.

I think statisticians are part of it, but it’s just a part. You also want to be able to visualize the data, communicate the data, and utilize it effectively. But I do think those skills—of being able to access, understand, and communicate the insights you get from data analysis—are going to be extremely important. Managers need to be able to access and understand the data themselves."

As habilidades destacadas pelo CEO de Economia do Google refletem bastante a proposta apresentada por Ben Fry em sua tese de doutorado intitulada Computational information design, defendida no Massachusetts Institute of Technology (MIT), em abril de 2004:

Computer Science - acquire and parse data
Mathematics, Statistics, & Data Mining - filter and mine
Graphic Design - represent and refine
Infovis and Human- Computer Interaction (HCI) - interaction

O profissional com esse perfil é o que o FlowingData chama de cientista de dados:

"(...) And after two years of highlighting visualization on FlowingData, it seems collaborations between the fields are growing more common, but more importantly, computational information design edges closer to reality. We're seeing data scientists - people who can do it all - emerge from the rest of the pack."

"(...) Think about all the visualization stuff you've been most impressed with or the groups that always seem to put out the best work. Martin Wattenberg. Stamen Design. Jonathan Harris. Golan Levin. Sep Kamvar. Why is their work always of such high quality? Because they're not just students of computer science, math, statistics, or graphic design.

They have a combination of skills that not just makes independent work easier and quicker; it makes collaboration more exciting and opens up possibilities in what can be done. Oftentimes, visualization projects are disjoint processes and involve a lot of waiting. Maybe a statistician is waiting for data from a computer scientist; or a graphic designer is waiting for results from an analyst; or an HCI specialist is waiting for layouts from a graphic designer."

meu comentário: a noção de cientista de dados mostra que cada vez mais o trabalho coletivo e a mistura de habilidades são indispensáveis para elaborar projetos para a cultura de rede. Isso significa que a internet reconfigurou a noção de formação técnica e teórica ao reunir conhecimentos de diversas áreas em apenas um profissional. Talvez, a recombinação de práticas possa guiar a pauta de revisão da formação jornalística.

A pensar,

LM