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I've also worked with actuaries and my impression has been different. Some of them have some skills, but it's very hit-and-miss, and it's not clear to me that t

I've also worked with actuaries and my impression has been different. Some of them have some skills, but it's very hit-and-miss, and it's not clear to me that the average actuary would compete with the average Master's in Data Science / Stats / CS in terms of effectiveness as a data scientist. Their big weakness is computational/programming skills. Many of them are simply unable to function outside of Excel. The SOA is trying to remedy this with new exams (of course) but my impression is that it's too little too late.

solumos 5y ago
this is true — as an analyst, I was severely reprimanded for writing data cleanup scripts since they couldn't be reviewed in vanilla Excel
- civilized 5y ago
  Incredibly depressing. I hope you got out.
ActualActuary 5y ago
I think it’s an unfair comparison. Of course the average actuary wouldn’t even come close to the average days scientist when it comes to data science skills. Just like the average doctor wouldn’t, the average lawyer wouldn’t, and the average banker wouldn’t. The problems they solve require very different skills. The problems I solve on a day to day basis have no need for data science. There are certain areas in my company where we use data science heavily, but in the areas we do need to use it we just use actual data scientists. The SOA, in my opinion, is going down the wrong path. Actuaries shouldn’t be trying to compete with data scientists. It has such little relevance to the work of most actuaries and in my opinion it’s just a way for the SOA to try and increase their revenues by jumping on a bandwagon. I agree with you “hit and miss” observation though. The exams are a barrier, but they’re not perfect. Plenty of mediocre people slip through the net. My company has roughly 100 actuaries. There are maybe 10-15 people that I’d consider very good at their job. The rest are just “meh”. I suspect this is the same in most fields though. Most companies now seem to have some sort of “data science” function. Unless the company is a tech or “data is the product” company, those data science functions don’t seem to contain the brightest data scientists. A friend of mine is a data science lead at retail company, and he’d be the first to admit he’s fairly mediocre. Most of their challenging work is outsourced to a specialist consultancy and their in house staff barely do any actual “science”.
- civilized 5y ago
  The question was about whether actuarial credentials should be positive signals in an application to a data science job. And my answer is: all else being equal, having more credentials is arguably good. However, all else is not equal. Having invested in actuarial credentials is a fairly strong signal of very limited computational/programming skills which are critical to a data science career. So the net signaling value of actuarial credentials in data science is actually negative. I'm well aware that data science is as awash with mediocrity as any other field, but not being able to function outside of Excel makes you mostly useless as a data scientist, not merely mediocre. I also agree with you that actuaries should not compete with data scientists, and should mostly stick to product, actuarial finance, reserving, etc. unless they desperately want to do data science, in which case they should switch to data science. > in my opinion it’s just a way for the SOA to try and increase their revenues by jumping on a bandwagon. It's worth noting that this is exactly what you'd predict if you buy my original thesis about the exams.
  - ActualActuary 5y ago
    I agree completely with your last paragraph. If I wanted to be a data scientist I’d be a data scientist. I don’t want my actuarial organisation wasting time and money trying to market us as “data scientists” when we are not data scientists. It’s a completely different job. It’s almost comparable to the profession deciding that we should now market ourselves as lawyers because we also contribute to writing contracts and treaties. I would argue though that being an actuary doesn’t automatically make you bad at anything outside of Excel. I’m not a data scientist, but I’m sure if I decided to go down that route my skill set would put me in a good position. I have a very good grounding in statistics and probability. I use R/Python quite heavily, regularly building models from scratch. I work with GLMs, Copulas, Monte Carlo simulation etc. I deal with big volumes of data and have to write efficient algorithms to deal with it. Most of my skills didn’t come from the exam path, but doing the exams also didn’t make me bad at all those other things. Just being an actuary obviously doesn’t mean you have those skills though, which is what I was getting at with my “hit and miss” comment.
    - 5y ago

solumos 5y ago

this is true — as an analyst, I was severely reprimanded for writing data cleanup scripts since they couldn't be reviewed in vanilla Excel

civilized 5y ago
Incredibly depressing. I hope you got out.

ActualActuary 5y ago

I think it’s an unfair comparison. Of course the average actuary wouldn’t even come close to the average days scientist when it comes to data science skills. Just like the average doctor wouldn’t, the average lawyer wouldn’t, and the average banker wouldn’t. The problems they solve require very different skills. The problems I solve on a day to day basis have no need for data science. There are certain areas in my company where we use data science heavily, but in the areas we do need to use it we just use actual data scientists. The SOA, in my opinion, is going down the wrong path. Actuaries shouldn’t be trying to compete with data scientists. It has such little relevance to the work of most actuaries and in my opinion it’s just a way for the SOA to try and increase their revenues by jumping on a bandwagon. I agree with you “hit and miss” observation though. The exams are a barrier, but they’re not perfect. Plenty of mediocre people slip through the net. My company has roughly 100 actuaries. There are maybe 10-15 people that I’d consider very good at their job. The rest are just “meh”. I suspect this is the same in most fields though. Most companies now seem to have some sort of “data science” function. Unless the company is a tech or “data is the product” company, those data science functions don’t seem to contain the brightest data scientists. A friend of mine is a data science lead at retail company, and he’d be the first to admit he’s fairly mediocre. Most of their challenging work is outsourced to a specialist consultancy and their in house staff barely do any actual “science”.

civilized 5y ago
The question was about whether actuarial credentials should be positive signals in an application to a data science job. And my answer is: all else being equal, having more credentials is arguably good. However, all else is not equal. Having invested in actuarial credentials is a fairly strong signal of very limited computational/programming skills which are critical to a data science career. So the net signaling value of actuarial credentials in data science is actually negative. I'm well aware that data science is as awash with mediocrity as any other field, but not being able to function outside of Excel makes you mostly useless as a data scientist, not merely mediocre. I also agree with you that actuaries should not compete with data scientists, and should mostly stick to product, actuarial finance, reserving, etc. unless they desperately want to do data science, in which case they should switch to data science. > in my opinion it’s just a way for the SOA to try and increase their revenues by jumping on a bandwagon. It's worth noting that this is exactly what you'd predict if you buy my original thesis about the exams.
- ActualActuary 5y ago
  I agree completely with your last paragraph. If I wanted to be a data scientist I’d be a data scientist. I don’t want my actuarial organisation wasting time and money trying to market us as “data scientists” when we are not data scientists. It’s a completely different job. It’s almost comparable to the profession deciding that we should now market ourselves as lawyers because we also contribute to writing contracts and treaties. I would argue though that being an actuary doesn’t automatically make you bad at anything outside of Excel. I’m not a data scientist, but I’m sure if I decided to go down that route my skill set would put me in a good position. I have a very good grounding in statistics and probability. I use R/Python quite heavily, regularly building models from scratch. I work with GLMs, Copulas, Monte Carlo simulation etc. I deal with big volumes of data and have to write efficient algorithms to deal with it. Most of my skills didn’t come from the exam path, but doing the exams also didn’t make me bad at all those other things. Just being an actuary obviously doesn’t mean you have those skills though, which is what I was getting at with my “hit and miss” comment.
  - 5y ago