[dima-quant]

AI is very good at standard and well defined problems but much less so with complex and vague. For example, currently available models cannot write or even port a full-feature compiler of a mature language without very custom tweaking and direct supervision. Even with multiple agents, it still remains just a tool, though quite powerful. As you already know physics and programming, data science can be a natural alternative that requires both skills. From my experience, many problems there are vague and most of the job is to actually make a proper representative dataset and translate vague requirements to something well defined. AI helps with the actual implementation, the other part remains mostly human.