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Isn't the real skill for a Data Scientist one of scalability and abstraction, from Data? While its critical to be able to get the data and make it more plastic,

by 001sky 14y ago

Isn't the real skill for a Data Scientist one of scalability and abstraction, from Data? While its critical to be able to get the data and make it more plastic, for measurement of metrics, real-time pricing, or even various weak-form predictive variables, its ultimately the analysis and understanding that is Critical to monetization/value extraction. And to build a good system for this level of data transparency, you need some good high-level understanding for clarity of vision. There are lots of people good at all manner Quants, but like the interview question, how much complexity can you explain in 5 minutes? is not one all answer equally. The ability to scale from granular detail to abstract levels of organization, meaning, and pattern recognition, are critical to extracting value in these contexts. Also, its not clear folks are using consistently the term vis a via scale/scope. Consider an anaolgue of knowledge and expertise (real estate example): L1 Architect> l2 Contractor> L3 Sub-contrator> L4 Builder/Laborer> Is Data scientist an Architect? Or the person that builds the building? Is he the guy that does the plumbing? Although the up and coming "quantitative system analyst" probably doesn't quite ring the same tune on a biz card. And most refer to lower level quant mastery, eg. social engineering or quantitative finance, as a "black art" not a science. Without a high level vision, the concept/title seems...grandiose, until you get to very extreme levels of skill. And then it makes sense.

EwanToo 14y ago
I think quite a few data scientists are taking the position that they're a specialist plasterer in your metaphor, someone who does one job very well, but can't help design the skyscraper they're working inside. Good plasterers get paid (and treated) pretty well, but they're never going to be the architects who designed the building.
- 001sky 14y ago
  You raise an interesting point here. A good (old world) plasterer is best thought of as an Artisan. This word has been lost in the modern era (Artist!=Artisan), but thats arguably at our loss. The "black arts" are inherently those that require practioners to get their hands slighltly dirty in the details.[1] _____________ [1] Alternatively, i'm starting to see the clearer picture: "Data Scientist" is more a contraction than a description. viz: "Data-Analytics-Literate Compter Science" becomes "Data_Science" if you just omit the middle terms. For marketing purposes, moniker "Scientist" is highlighted as status signifier (Academically ~akin to "Artist").

by 001sky 14y ago

EwanToo 14y ago

I think quite a few data scientists are taking the position that they're a specialist plasterer in your metaphor, someone who does one job very well, but can't help design the skyscraper they're working inside. Good plasterers get paid (and treated) pretty well, but they're never going to be the architects who designed the building.

001sky 14y ago
You raise an interesting point here. A good (old world) plasterer is best thought of as an Artisan. This word has been lost in the modern era (Artist!=Artisan), but thats arguably at our loss. The "black arts" are inherently those that require practioners to get their hands slighltly dirty in the details.[1] _____________ [1] Alternatively, i'm starting to see the clearer picture: "Data Scientist" is more a contraction than a description. viz: "Data-Analytics-Literate Compter Science" becomes "Data_Science" if you just omit the middle terms. For marketing purposes, moniker "Scientist" is highlighted as status signifier (Academically ~akin to "Artist").