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  #31  
Old 11-30-2018, 11:33 AM
Fracktuary Fracktuary is offline
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What are the chances that the OP doesn't respond to Westley's fire analysis ?

Last edited by Fracktuary; 11-30-2018 at 11:41 AM..
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  #32  
Old 11-30-2018, 11:50 AM
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Resume incoming
Lol we are hiring.
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  #33  
Old 11-30-2018, 12:03 PM
Dr T Non-Fan Dr T Non-Fan is offline
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What are the chances that the OP doesn't respond to Westley's fire analysis ?
Not sure of the chances, but isn't that style called "FJM"ing? (As in "Fire Joe Morgan," a former web site that would take down crappy sports takes one sentence at a time?

OP just got 105.56% sexier, imo.
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  #34  
Old 11-30-2018, 01:03 PM
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I think it depends on the company. There seem to be parallel positions these days all the way up to VP. I don't see too many data scientists equivalent to chief actuary (Chief Data Scientist?) and oftentimes the most senior data scientist reports to the CA, so I suppose there. If the analytics department is completely separated from actuarial and large, I suppose there would be a position parallel to CA.

I don't see many DS executives either, but actuary executives are fairly common.
Yes, I agree with this. I don't see DS people at an exec table at any point. There's always the accounting or banking background person, there's always at least several with underwriting background, and at least with reinsurers seems more common now to have 1+ with actuarial background. I don't see a DS in that group and not just based on immaturity of the profession.

I just think their work is more "back office" and also more prone to constant change and turnover. Similar things are said about IT.
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  #35  
Old 11-30-2018, 02:06 PM
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are data scientists better than actuaries and supposed to get paid more in the first place?
I think I've mentioned something like this before but compensation feels like by percentiles:

Bottom 25% DS << Bottom 25% Actuarial - Exams / Credentials creates perceived value and lower DS are usually just analysts in disguise.

25% - 50% DS == 25% - 50% Actuarial - Skill set starts to break even with general ability to pass an exam.

50% - 75% DS > 50 - 75% Actuarial - advanced degrees, tech companies, start-ups, this is a landmine for compensation

Top 25% DS ?? Top 25% Actuarial - field is too young to compare adequately, but I know that top AI researchers are making quite a bit.

These numbers are rough, but it is fair to say one does not trump the other.

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Your leverage, and the basis for your pay, is your skill set. This is true for actuaries, and much moreso in DS.
I agree with this 100% and pretty much the rest of what Westley said. Only post OP needs to pay attention to.

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What's the ceiling for a data scientist at an insurance company? I'd have to believe actuaries have a much higher ceiling, have people thought about this?
The problem is you're trying to compare an entire profession against a subset of individuals from another profession who work under that limited scope.

However, I would assume that most data science jobs at insurance companies are underdeveloped and mimic something such as the OP's role as a business analyst. Clearly, these shouldn't be making more than actuaries. As for more developed companies, I would not be surprised if salaries are fairly equal across the earlier ranks. Overall, with all the bias included, actuaries >> data scientists with respect to only the compensation component when it comes to insurance companies.


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I wonder if there's some age bias too. I mean the actuarial profession has been around for longer and DS is fairly new, so a lot of the senior positions will be held by actuaries with decades of experience.
I'm glad that someone on an actuarial forum could recognize this.

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OP just got 105.56% sexier, imo.
RN, lol.

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Yes, I agree with this. I don't see DS people at an exec table at any point. There's always the accounting or banking background person, there's always at least several with underwriting background, and at least with reinsurers seems more common now to have 1+ with actuarial background. I don't see a DS in that group and not just based on immaturity of the profession.
If we're keeping the lens on the insurance industry alone, I'm likely to agree with you. However, while it might not all be based on immaturity of the profession, a healthy chunk probably is.

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I just think their work is more "back office" and also more prone to constant change and turnover. Similar things are said about IT.
In general, I disagree but I can imagine how at some insurance companies this could be the perception of what data science work is about. Probably a mixture of poor data scientists as well as people afraid of a business evolving.

-Riley
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  #36  
Old 11-30-2018, 05:19 PM
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I think I've mentioned something like this before but compensation feels like by percentiles
Riley would know better than me, but his percentiles also feel right for me. However, it's a bit confusing because it's pretty straightforward to define who is an actuary and who is not - basically, if you're an actuary, you're taking exams as part of your job or you're credentialed. For DS, some people are doing DS, some are somewhat doing it or it's a part of what they're doing, some have titles but it's not really what they do at all, it's much more squishy because there isn't a credentialing process that defines what it is.

I suspect* that, regardless of what the OP is actually doing or how DS/actuarial/business analytics it is, management at his company doesn't view his work as being comparable to a true DS position, so they don't think they need to pay him commensurate right now. Maybe their view is more like "Let him get some projects going and build his skills, and then we'll pay him"; or maybe they're clueless, or who knows**. Not all that different from hiring an EL actuary - you give him a title but he's totally clueless and you're just expecting that he'll grow into the title that you've already given him.

*Lots of conclusions drawn from a very small amount of data, so grains of salt required here
**If OP doesn't know the answer to this, he needs to find out
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  #37  
Old 11-30-2018, 05:24 PM
Fracktuary Fracktuary is offline
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Riley would know better than me, but his percentiles also feel right for me. However, it's a bit confusing because it's pretty straightforward to define who is an actuary and who is not - basically, if you're an actuary, you're taking exams as part of your job or you're credentialed. For DS, some people are doing DS, some are somewhat doing it or it's a part of what they're doing, some have titles but it's not really what they do at all, it's much more squishy because there isn't a credentialing process that defines what it is.

I suspect* that, regardless of what the OP is actually doing or how DS/actuarial/business analytics it is, management at his company doesn't view his work as being comparable to a true DS position, so they don't think they need to pay him commensurate right now. Maybe their view is more like "Let him get some projects going and build his skills, and then we'll pay him"; or maybe they're clueless, or who knows**. Not all that different from hiring an EL actuary - you give him a title but he's totally clueless and you're just expecting that he'll grow into the title that you've already given him.

*Lots of conclusions drawn from a very small amount of data, so grains of salt required here
**If OP doesn't know the answer to this, he needs to find out
OP seems to have a sense of entitlement tho. Which is a bad thing to wear on your sleeve.

I was like this earlier in my career and it did not help. Had to do some soul searching in order to not let it affect my prospects.

Last edited by Fracktuary; 11-30-2018 at 05:28 PM..
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  #38  
Old 11-30-2018, 06:52 PM
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(Chief Data Scientist?)
Or Chief Algorithms Officer? e.g. Stitch Fix
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  #39  
Old 11-30-2018, 07:44 PM
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Or Chief Algorithms Officer? e.g. Stitch Fix
Often titled Chief Scientist too.

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  #40  
Old 12-01-2018, 04:54 AM
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I don't mean to throw shade but in my experience (i.e. I can't back it up with hard facts but it certainly feels rights anecdotally) is that the insurance industry is seen as sleepy by data scientists types. The best ones will pursue other industries where they are more in demand and less likely to be hampered by a stodgy profession like actuaries. On top of that, compensation in insurance for talent is lacking. So the data scientists that actuaries work with on a day to day basis have passed through several filters such that the distribution of talent for data scientists within the insurance industry is different than without.
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