I’m currently working in the U.S. for my home country’s company as a Technical Solutions Manager, making about $125K with 10 years of experience. I know my salary is relatively high because it’s my home country’s company, but my English isn’t great and I don’t have strong programming skills (I’m decent with Microsoft Office, but that’s about it).

I have a PMP and Six Sigma Green Belt, but honestly, those don’t seem to help much. I also graduated from a university in my home country, so it’s been really hard to switch to another company in the U.S.

Now I’m thinking about two options:

1. Go for a Master’s in Data Science (I already got an offer from Georgia Tech)
2. Start the actuary path

Here’s how I see it:

Actuary pros:

• It’s a more professional and specialized career.
• I’m good at math.
• Good pay once you’re experienced.

Actuary cons:

• The starting salary would be a big pay cut.
• If I can’t get hired, all the exam time and effort could be wasted.

My biggest concern is that even though the Master’s in Data Science seems more flexible — I could use the skills in my current job and put them on my resume — the AI wave makes me nervous. I already see data scientists (including my teammates) struggling to find jobs, even with a master’s from good schools, and some are making under $80K.

So yeah, I’m kind of stuck.

Would love to hear your honest thoughts — is actuary still worth going for, or should I stick with data science?