I'm a third year college student at a top US university studying math and computer science. I'm struggling to decide between pursuing a PhD in AI safety research or working at a quant firm/E2G. A third wildcard career path would be a data-informed policy role where I could use my quantitative skills to help policymakers, but I've struggled to find roles like this that are both high impact and technically interesting (would love some help with this!).
I will be working at a quant trading firm (one of Citadel, Optiver, etc.) next summer as a software engineer and I currently work in an AI research lab at school, so I'm well set to pursue both career paths. It's a question of which path is higher impact and will be the most rewarding for me. I'll try to list out some pros and cons of the PhD and E2G routes (ignoring data-driven policy roles for now because haven't found one of those jobs).
Quant Firm E2G Pros:
Quant Firm E2G Cons:
AI PhD Pros:
AI PhD Cons:
I'd love to hear your thoughts on deciding between these roles as well as any ideas for the wildcard option that are worth exploring!