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Who makes more money in the long run: an Actuary or a data scientist?

A question about money and that too in Actuary is your favourite! I know.

Well it just appeared while browsing quora and the Answer blew me away!

As per Alex Kelly, A user of Quora,

 I’m a master’s student in data analytics, but I have also interned as an actuary and passed a few of their exams. Here are my observations of both fields:

Though data scientists have higher starting salaries, entry-level positions almost always require a graduate degree. Actuaries on the other hand get most of their training on the job. Because actuaries receive continuous self-education while working, it’s not uncommon to see up to $10k raises every year. A data scientist does the majority of their training in graduate school, which is why they have much higher starting pay but with lower annual salary advancement.

An average actuary starts at $60k right out of undergrad. After two years they have a couple more exams under their belt, putting them at $80k. Now this is when the data scientist is prepared to enter the workforce. They’ve spent 2 years doing their master’s, putting them $40-60k underground in graduate loans. They’re making a solid $80-$100k, but have to live at essentially the same pay level as the actuary (or lower) for the next few years to pay off the extra debt. 

 

As for long-term, it really depends. Some actuaries have trouble passing even 1 exam every year, in which case it could take 10 years just to get your credentials, and maybe max out around $150k. If you can motivate yourself to pass two exams a year (which I found doable with the amount of study time most companies give), you can move up quickly and be making $200k in 10 years.  On the other hand, even a really good data scientist may not make that much at their maximum lifetime salary (max out around $150, possibly $200k managing a large team). Actuary salaries continue to increase linearly with time, even after the data scientist’s has leveled off. Experienced actuaries get opportunities to move into high-management positions like VP/chief actuary, and ultimately CFO/CRO and CEO. Data scientists may make it to CIO/CTO positions. Both actuaries and data scientists have the tools to start their own companies as well.

Also Read: Insurology releases app for Blogs & Forums

TL;DR – Unless you’re passionate about programming or dislike studying/taking exams, actuary seems like the better option (financially) in the short run. As for long run, it really depends on your capacity to pass actuarial exams and/or your hunger for management.

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And on the other hand

As per Henry Siegel, whose profile explains, I’ve been an actuary for over 45 years.

It all depends on the individual.  If you are talented, either can make a lot of money. 
So, what you’re thinking as of now? Data Scientist or Actuary? 😉
Do share your thoughts 🙂
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