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I am split between these options and need a little guidance.

1. Graduate w/ 3+ actuary exams ➡️ El role

2. Graduate ➡️ Ms in Data science ➡️ DS Field


Salary is first priority and although actuary has a higher mean income (supposedly) i’ve consistently seen much higher salaries with the MS. It seems like actuary has not kept up with other fields regarding salary and if i’m going to be studying and taking exams for the next decade, why not get the MS instead and get paid the same if not more?

Input would be appreciated!
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For people like you, first convince yourself why you don't want to be a SWE making banks at FAANG. Then we can talk about act sci vs DS.

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>why not get the MS instead and get paid the same if not more?

MS costs money and time. If you factor that in, DS isn't really ahead.

One major benefit of act sci is you are fairly certain to reach 6-figures with a college degree (and exams, of course).

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Lastly, let's not forget actuary and DS have different career trajectories. Actuary sits right at the core of insurance business whereas, unless ML is the core business, DS are usually auxiliaries to the business.
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This is anecdotal - but every actuary I know (that stuck with it) is very well paid

For me, I wish I went that route because of the structure. Pass an exam = get a raise
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Whichever one you're more interested in is probably going to pay off more long term, even in terms of salary. Harder to advance in a field if you don't enjoy it. My impression of actuarial science is that it is more structured and you will probably have more job security and a clearer path for advancement assuming you can pass the exams. You are kind of locked in to working in insurance though, which many find boring. And taking exams for years is kind of unappealing, at least to me.
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I changed my major from act sci to stats midway thru my undergrad and now work as a DS (no grad school). The real eye-opener for me was when I was interviewing for actuarial internships at a few big insurance companies. The thought of studying for exams after work + running excel formulas all day did not appeal to me and I did get kind of an archaic feel from it.

I’m very happy (so far) with my decision to work in DS/analytics as apart of my job description is to keep up with the cool new tech and how to apply it in my work. I much prefer that kind of learning and discover over an antique exam process.

I have colleagues who are actuaries and they’re doing great as well, I’d recommend to interview a couple internships and try to get a feel for what you prefer.
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Actuarial major here who is now a DS at an insurance company and I’ll say two things:

1) I see LOTS of actuaries career jump over to the DS side but have never seen the reverse.
2) My credentialed actuary wife makes a lot more than me. Exam raises really add up.
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Actuarial exams are soul sucking, especially while working, and usually worth it. Depends on what you want.  Data science is also a lifetime of learning(less assessments), but there’s higher variance in job security, pay, and work life balance. This can be both a good thing and bad thing.
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Actuary here in the Property and Casualty space:

The accreditation process through exams is a long one but most companies have programs that pay for the exams and study materials as well as provide generous study hours, 100-200 per sitting. I’ve seen people reach accreditation in their mid-20s by flying through the exams, but is usually completed by late 20s/early 30s. You’ll lose weekends and social life when sitting for exams but as others have said, handsomely rewarded for each pass. Typically, exam raises are around 5-10% salary increase, and milestone credentials 10-20% in addition to annual merit increases and bonuses. In a MCoL city, a new fully accredited actuary could be making 140-200k annually. You do have obligations as part of the society for continuing education, but the on site locations to complete those can be fun. Recently, they did Hawaii.

An accredited actuary has great career opportunities to move into management and are often top candidates because of their deep understanding of both the technical and business side, and have seen peers move out into senior leadership roles earlier relative to their non-actuarial counterparts. There are options for great pay as subject matter experts within as well so don’t think you need to go management route. If you go the expert route and are fully credentialed, you can float through your career making great money in a stress free environment without working more than 40 hours a week. Either way opens the path to promising compensation and fantastic job security.

Because insurance is regulated and rate changes need to be approved by departments of insurance, the Machine Learning component of the role is constricted to fewer rudimentary algorithms and supplemented with using business judgment to drive decisions. The governing actuarial societies recognize this and are currently advocating for enhanced modeling sophistication to a degree of success. Some examples of models used: Insurance Rating Plans, Territorial Analysis, Bind/Retention. Insurtech is a budding industry that has more use cases. Because insurance products are a zero sum game, it’s definitely a fun and creative exercise to get the best risks on your books vs. competitors. I really enjoy the work content.

The glaring con is that you are primarily restricted to the insurance industry, though some actuaries  have moved into risk management in financial institutions. Either way, this may limit the places you can work, but the adoption of working remotely alleviates this. I have seen peers leave the profession due to wanting heavier coding or pure data science roles. The exams are not for everyone either and while the credentials are well respected in the industry and relatively unknown or obscure outside of it.

You could probably make more money going into a Data Science role after MS, but you’ll be paying more for it and entering a potentially saturated field. I think the actuarial salary will catch up and be competitive after you are fully accredited. DWSimpson has an actuarial salary survey you could view to check salaries.

Hope that helps!
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I graduated undergrad with two exams and then did an MS DS degree after a couple years working as an underwriting analyst. Now I’m at another insurance working with actuaries on reinsurance as a DS analyst making like 10-20k more. There’s also the CSPA exam through the ICAS I think that has a lot of neat crossovers from actuarial exams and data science work that I’ll probably try this year.
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I had a similar decision. I took the FM actuarial test and did a hobby data science project when I was working one summer. Self-learning a bit of both could give you enough info to figure out which one you like more
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An ASA has the equivalent education of a data scientist imo.  With an ASA you can expect 120-130/year.  A DS with a masters and 2-3 years of experience can expect 110-140 or 150-225 if you're in tech.  You'll be more stable with an ASA as I think DS are overpaid.  Running models is repeatable and simple.  FSA will be even more secure and pay more.
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