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Teaching me what I don't know is what I want with all of my engineering hires. I want people better than me who will tell me why my architecture isn't ideal or

Teaching me what I don't know is what I want with all of my engineering hires. I want people better than me who will tell me why my architecture isn't ideal or whatever the case is.

mindcrime 9y ago
Yes, but I'd argue that's on a different level from "teach us why we need an 'architecture'" or "teach us how to use this 'data science' stuff". Some people are trying to be buzzword compliant when they don't actually understand the buzzwords. Ya know? Or maybe there's a better explanation for asking for a candidate with a Ph.D. in Statistics to create a linear regression model in Excel. Because truth is, for many companies that's all they need.
- cat199 9y ago
  I get that it's difficult to get these gigs.. But also recall, that there are alot of people with general computer backgrounds and a whole lot more real-world work experience who could pick up the basics of data scicnce stuff as well.. Places where these jobs tend to be needed are often very highly placed and very strategic, with the decisions being made based on the data very critical to the overall company health. Some of what is being requested by requiring this level of credentials is real-world work experience and a certain level of maturity/professionalism that is often implied by this as well.. If the level of skill is basic enough that any other regular employee could learn it in short order, why wouldn't they and then have the cushy 'sit around and play with numbers all day' job too.. There needs to be enough 'there there' to placate internal politics as well.. Further, having a more advanced person would also likely need to be taking leadership roles in picking and rolling out solutions with long term costs associated with them, training other employees, etc, which also comes with the professionalism/experience part..
- gaius 9y ago
  a Ph.D. in Statistics to create a linear regression model in Excel Linear regression, logistic regression and k-means clustering, if you can get a project into actual real-money production on one of those, you are already well ahead of 90% of data scientists. And these techniques are decades old!

Teaching me what I don't know is what I want with all of my engineering hires. I want people better than me who will tell me why my architecture isn't ideal or whatever the case is.

mindcrime 9y ago

Yes, but I'd argue that's on a different level from "teach us why we need an 'architecture'" or "teach us how to use this 'data science' stuff". Some people are trying to be buzzword compliant when they don't actually understand the buzzwords. Ya know? Or maybe there's a better explanation for asking for a candidate with a Ph.D. in Statistics to create a linear regression model in Excel. Because truth is, for many companies that's all they need.

cat199 9y ago
I get that it's difficult to get these gigs.. But also recall, that there are alot of people with general computer backgrounds and a whole lot more real-world work experience who could pick up the basics of data scicnce stuff as well.. Places where these jobs tend to be needed are often very highly placed and very strategic, with the decisions being made based on the data very critical to the overall company health. Some of what is being requested by requiring this level of credentials is real-world work experience and a certain level of maturity/professionalism that is often implied by this as well.. If the level of skill is basic enough that any other regular employee could learn it in short order, why wouldn't they and then have the cushy 'sit around and play with numbers all day' job too.. There needs to be enough 'there there' to placate internal politics as well.. Further, having a more advanced person would also likely need to be taking leadership roles in picking and rolling out solutions with long term costs associated with them, training other employees, etc, which also comes with the professionalism/experience part..
gaius 9y ago
a Ph.D. in Statistics to create a linear regression model in Excel Linear regression, logistic regression and k-means clustering, if you can get a project into actual real-money production on one of those, you are already well ahead of 90% of data scientists. And these techniques are decades old!