As the brother of an actuary, one of my favourite jokes is "Actuaries are people who tried accountancy but found it too exciting." :)

I started my programming career at an actuarial consultancy. My favourite was "There was once an actuary who was so boring, all the other actuaries noticed".

Actually I found the partners to be great people. I think some went out of their way to be unlike the image. I also think their particular skills can be applied more widely than the profession normally encompasses. A lot of the actuaries I met backed horses and I'm sure they had an unfair advantage!

AIUI, in the UK at least, it, along with veterinaries, require the longest period of training before chartered qualification.

my dad always phrased it as "Actuaries are people who wanted to be CPAs but failed the personality test"

I'm also an actuary, and I agree with all of this. I personally had a better experience with my undergraduate coursework thanks to a flexible program - I took no exam prep courses and close to 30 credits' worth of CS courses - but it's definitely the norm for an actuarial science major to essentially be an exam prep major.

There are lots of data science roles at insurance companies, many of which seek out current and former actuaries, so that's probably the easiest foot-in-the-door role to transition out of the field if that's more in line with what you're looking for. However, I'm sure those roles are pretty boring as data science goes.

I started an actuarial science degree too and this is exactly my experience. But I then ditched it and took a different path. It was quite a risk at the time (not an actuary joke, oh my god just no).

I was 18 and dumb and knew I was good at mathematics and that it was a good career. But it was actually quite dull and, like you say, very robotic. So I was able to switch degrees to pure math and then computer science and then crypto. I’m glad I did. It’s more interesting, challenging, and despite it never being my goal, more well-paid anyways.

Basically it just strikes me as a very safe, stable, dull job. Also what kind of 18 year old was I to want this?!

I also did the same as an 18 year old. It wasn't the math that got me at the time, it was the hardcore statistics. This isn't the mid-tier stuff the data science people get paid for, these are the ridiculous sort of probability problems that just bend your mind trying to wrap your head around it.

I think it's a very powerful job background to have if you ever want to get into investing hardcore. The financial background it gives you is incredibly helpful for making investment comparisons. I still use the stuff that I learned when studying for the FM test for personal finance decisions like paying off mortgage vs student loans vs various basic investments.

what do you do in crypto? As a programmer I find bitcoin really fascinanting and was thinking about learning the codebase and trying to contribute something to community but I find it really hard to do so...

A couple years ago, "crypto" would have been short for cryptography. These days, it can be that or the cryptocurrency madness.

In this case, I thought Moodles meant cryptography. Also, I'm not sure whether you're joking by choosing to understand it as cryptocurrency. Or perhaps you're both talking about cryptocurrencies and I'm the only confused one here...

I mean cryptography.

Former actuary here. Let me try to explain some of the frustrations that occur in the profession:

Technical ownership is distributed from the top down and can not be overridden from bottom-up process improvements. Even if it made sense to integrate two departments that regularly pass each other data, that will be fought because that interferes with someone's corporate fiefdom.

There is no clear high-level diagram of how the whole company functions. So unlike a web-app with a client-frontend-routing-backend-database pipeline that a smart 15 year old could learn to conceptualize, instead you're expected to learn the inter-process requirements in a piecemeal fashion, one detail at a time as it arises in a weekly task. In the best case, this big picture starts to emerge ~5 years into a full time job. In the more likely case, your tasks never expose you to some part of the company's operations and they remain a blackbox and you'll be unable to reason about.

While inter-process communication remains opaque, complexity within each process proliferates. If you do life insurance, you need to support every product you sell for fifty years, so you deal with often poorly documented product rules and hard core legacy systems. Note - you can't deprecate anything because must honor those complicated agreements made decades ago.

Basically the frustrations boil down to doing interesting systems/data work but with being forced to do it in a worst-practices fashion.

It also doesn't factor in the completion % as risk. The harder the degree, the more chance you have of being saddled with debt and no prospects. ( I may have gone the actuarial science route, meanwhile tinkering with websites as a hobby, without considering websites as a career, circa 2004, then failing out of actuarial science, later getting serious about the web stuff ).

I also tried actuarial science out, just barely failing the first test twice (you need 6 out of 10 to pass, I got 5 both times). I say this as a software engineer: actuarial science is hard. There is a ton of material and the tests are easily the most insidious you will ever take.

To give an example of the insidiousness, imagine a calculus problem that has about 6 or 7 steps required to solve this - calculate the derivative, then reduce it, and maybe a sum after that. Actuarial science problems are like that as well. The tests (at least the first two) are mutiple choice, 5 answers. Each “choice” has one of two situations for wrong answers.

- The answer is the correct number but it’s the number you arrive at stage 5 of solving the problem (instead of the final stage), so you are tricked into thinking you are done when you actually have more steps to go

- the number is what you arrive at when you make a common mistake

- some combination of the above

I will say I was told (at least) that passing one or two of the tests is enough to land you a full time entry level job (and entry level for an actuarial scientist is still really good)

If you think that's fun, the FSA exams are a whole new level of crazy. The math mostly goes away outside of financial statement type stuff, and in comes thousands of note cards on bland regulations (stuff like FAS106).

But, people have to be weeded out in some way, amirite?

"Completely worthless" is not what comes to mind, when it provides your living.

If it doesn't fulfil you, and you have a math degree, why not change careers?

Completely worthless is in the context of my degree in actuarial science. As someone else said, it’s an exam prep major. I learned more problem solving and critical thinking skills in mathematics, and I’ve found that much more helpful in my career.

I have worked as a health actuary for the past 6 six years with degrees in both math and computer science. I am happy with my career choice. Prior to this I did work several years as a programmer and decided while I enjoy programming it is not something I want to do all day every day.

My current position allows me to make use of some of those skills along with learning a wide variety of other skills. Although from the sounds of other people's posts I might be lucky in my current position, where I do have variety and challenges and more than only routine work.

But from an education stand point I am glad that I went the route that I did given the additional skills rather than an actuarial science degree. The one downside is that it has made the exam process a little longer.

How was transitioning from programming to an actuary?

I went into actuarial work very long ago, and I cannot say anything about how it goes now, as I have long been away from it. When I started, an actuarial degree was a rarity for an actuary. I was glad to study something more challenging and engaging in school before entering into a profession that so rarely requires any knowledge of anything more than the conventions of an arcane art. How is it different now? What do life insurance actuaries do now that there are so few life companies? Same question for casualty insurance companies? What do pension actuaries do now that there are so few defined benefit plans? What percentage of practitioners now have actuarial degrees? How do you stay awake at the professional meetings?

What if you don’t want to “learn to think,” whatever that means, but instead want to learn how to do a well in a low cost of living area?

By all means, if you can get through the exams, you will be left with a low stress, well paying job at an insurance company, and you’ll likely have great job security. There is absolutely nothing wrong with that. But as Christensen talks about in one of his books, those are hygiene factors. You can find fulfilling, motivating work as an actuary, but salary should not be the main reason for choosing a career.

> salary should not be the main reason for choosing a career.

Why?

Because of the law of diminishing marginal utility as applied to income [1]? Once you hit a certain level of income, other factors can start to outweigh the marginal utility of a higher salary.

For example, I could maybe make more money working in high frequency trading, but I don't want to. It wouldn't be a life-changing amount of money, and I value the ability to work on interesting problems in the open, with less concern for ethical issues†, over the potential additional income.

[1]: https://qz.com/1211957/how-much-money-do-people-need-to-be-h...

†I don't want to start an argument about whether HFT is unethical; in fact, I don't think it is necessarily unethical. I'm just saying it would always be at the back of my mind.

Professor Christensen says it better than I ever could: “Motivation factors include challenging work, recognition, responsibility, and personal growth. Feelings that you are making a meaningful contribution to work arise from intrinsic conditions of the work itself. Motivation is much less about external prodding or stimulation, and much more about what’s inside of you, and inside of your work.“

I am guessing it's easy to transition to machine learning / data analysis and make 20-40% over what senior devs make. At least that's what I see in my area.

I would be really impressed if someone with an actuarial science degree has any experience with machine learning. That is not a skill that is taught outside of self learning or an absolute need. It may be more applicable in a property casualty company where there are things like telematics.

The society of actuaries is now testing basic analytics and R programming as part of the exam system. The Introduction to statistical learning book is on the exam syllabus.

You are correct, and I view it as an attempt to remain relevant in an area they feel threatened by. We will see what the exam ends up being like, but I have little faith in the SOA being able successful test someone’s experience in “predictive analytics” with a five hour proctored exam.

Yeah. Definitely seems like their “predictive analytics” push is reaction to the rise in popularity of “data science”.