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  #141  
Old 12-11-2017, 04:17 PM
royevans royevans is offline
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You don't say?



-Riley
At least I didnt say "The difference between a data scientist making 300k and a data analyst that is making 50k is 250k."
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  #142  
Old 12-11-2017, 04:21 PM
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At least I didnt say "The difference between a data scientist making 300k and a data analyst that is making 50k is 250k."
I don't think you're even aware of the scope of what complex work is in the scenario, but I'd love for you to prove me wrong.

-Riley
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  #143  
Old 12-11-2017, 04:22 PM
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"/" usage here shows how clueless people are to what "real" data science work is.

If the titles are accurately represented, a data analyst cannot do what a data scientist can do.
You mean there's concern that a job title can misrepresent the minimum qualifications of a person? If only there were some way to validate the minimum level of education a person must have.
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  #144  
Old 12-11-2017, 04:29 PM
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Colonel Smoothie Colonel Smoothie is offline
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Software engineers have an even bigger variance in compensation. Do they also have these conversations on who is and isn't a software engineer?
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Don't you even think about sending me your resume. I'll turn it into an origami boulder and return it to you.
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  #145  
Old 12-11-2017, 04:32 PM
nonlnear nonlnear is offline
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Software engineers have an even bigger variance in compensation. Do they also have these conversations on who is and isn't a software engineer?
Maybe not over that particular term, but some of them have long masturbatory sessions about who is - and who is not - a full stack developer.
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  #146  
Old 12-11-2017, 04:34 PM
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You mean there's concern that a job title can misrepresent the minimum qualifications of a person? If only there were some way to validate the minimum level of education a person must have.
You're right. A system should be put in place for those who aren't skilled enough to gauge the skillset of a candidate on their own. This puts the pain of the hiring process on the credentialing society. What a comfortable and easy world to make decisions in! Check off the boxes: FCAS/FSA? Check! Years of experience > X? Check! GPA > Y? Check!

At my current place of employment, there is no struggle in evaluating if someone is a 50k data analyst or a 200k data scientist and we don't even look at the resume during the interview process!

If insurance companies are hiring data scientists using actuaries to evaluate them, then I can imagine there is a struggle where the skillsets diverge. Much easier to just ask the SOA/CAS if they "meet requirements".

-Riley
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  #147  
Old 12-11-2017, 04:36 PM
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Software engineers have an even bigger variance in compensation.
Source?

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  #148  
Old 12-11-2017, 05:56 PM
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Originally Posted by whoanonstop View Post
You're right. A system should be put in place for those who aren't skilled enough to gauge the skillset of a candidate on their own. This puts the pain of the hiring process on the credentialing society. What a comfortable and easy world to make decisions in! Check off the boxes: FCAS/FSA? Check! Years of experience > X? Check! GPA > Y? Check!

At my current place of employment, there is no struggle in evaluating if someone is a 50k data analyst or a 200k data scientist and we don't even look at the resume during the interview process!

If insurance companies are hiring data scientists using actuaries to evaluate them, then I can imagine there is a struggle where the skillsets diverge. Much easier to just ask the SOA/CAS if they "meet requirements".

-Riley
It's data scientists all the way up
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Don't you even think about sending me your resume. I'll turn it into an origami boulder and return it to you.

Last edited by Colonel Smoothie; 12-11-2017 at 05:59 PM..
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  #149  
Old 12-11-2017, 07:11 PM
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Quote:
Originally Posted by whoanonstop View Post
You're right. A system should be put in place for those who aren't skilled enough to gauge the skillset of a candidate on their own. This puts the pain of the hiring process on the credentialing society. What a comfortable and easy world to make decisions in! Check off the boxes: FCAS/FSA? Check! Years of experience > X? Check! GPA > Y? Check!

At my current place of employment, there is no struggle in evaluating if someone is a 50k data analyst or a 200k data scientist and we don't even look at the resume during the interview process!

If insurance companies are hiring data scientists using actuaries to evaluate them, then I can imagine there is a struggle where the skillsets diverge. Much easier to just ask the SOA/CAS if they "meet requirements".

-Riley
1) So your place of employment is representative of every other one? Sample size of 1!
B) If employers were the only ones that needed that validation, then that might be sufficient. If someone is looking for consulting via data scientists, how do they tell? "Trust us, we know what we're doing" only gets you so far.
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  #150  
Old 12-11-2017, 11:55 PM
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The difference between a data scientist making 300k and a data analyst that is making 50k is that the 300k one is doing much more complex work. It's a grey area about the difference between an analyst and a scientist but to me it just seems like one of those fields that people who are good at what they do will make a lot of money and people who don't will make the same as most other white collar jobs.

I think its fine if a 50k data scientist calls himself a data scientist, but there is prestige that goes along with some data scientist jobs and not others.

e.g. a data scientist at Amazon making 300k != a data scientist at some regional bank making 50k in terms of tasks and skills of the job.

The field seems like there are many subprofessions with varying amounts of pay and knowledge required. But nonetheless, I think they are all still data scientists/analysts.
I don't consider "data scientist" to be a profession. You're basically contradicting yourself here. The fact that nobody has a clue what the hell a "data scientist" is supposed to mean is proof that it's not a well defined profession. A profession is like an actuary,accountant, lawyer, doctor, engineer, etc. People working in that profession all have similar educational and professional qualifications and they're usually members of some organization which sets "professional" standards. People know the difference between a nurse, a family doctor and a surgeon. People know the difference between a bookkeeper and an accountant. People know the difference between a lawyer and a notary. Personally I think it's sad/pathetic that people abuse the label "data scientist" to glamorize some random IT job.
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