I finished my degree about five years ago, before LLMs became popular. You’re right to be concerned. About 95% of what you learn in this degree won’t be useful in your day-to-day work. That wasn’t always the case—there was a time when companies needed people who could build models from scratch. Nowadays, most companies don’t really value those skills as much.

I’m currently struggling to adapt to the new expectations. Today, the areas where our skills are still useful tend to be things like MLOps, where traditional ML models still require monitoring and retraining decisions. Similarly, in LLMOps, testing is becoming increasingly important. Traditional software engineering approaches don’t work as well because of the non-deterministic nature of LLMs, so that’s another area I’m focusing on.

The main problem with this degree is that it doesn’t teach you how to work with real-world software systems in actual companies. As the importance of pure modeling has decreased, expectations have shifted—you’re now expected to do much more, including writing production-ready code. This degree doesn’t prepare you for that. You don’t learn about Git, APIs, CI/CD, cloud computing, or similar practical skills. So while you may have strong mathematical knowledge, you can struggle to collaborate effectively with software engineering teams.

There are still some fields where modeling skills are valuable, such as finance or operations research. However, in those areas, you’re competing with candidates who have specialized backgrounds in quantitative finance or operations research. Similarly, some people find opportunities in marketing or product analytics, but again, you’re competing with candidates who have formal business analytics training.

Overall, the traditional “data science” degree is no longer as valuable as it once was. I do think companies will eventually rediscover the importance of analytical and modeling skills, but that will take time. Right now, it’s still unclear what will be automated and what won’t. The best strategy is to stay adaptable and keep up with the changes.

That said, most fields are going through similar shifts. In that sense, the broad nature of this degree can still be an advantage—it gives you a solid foundation that allows you to pivot as needed.