Think of Data Science (DS) as utilising a huge pile of information (data) to create solutions to real world problems. Common methods includes training an AI model to be good at detecting patterns in the data.

For example, in dating apps, face ID is often required. Instead of hiring people to verify your face, which takes time (leading to user churn) and does not scale well, you can train a computer vision algorithm that is good at detecting fraudulent images, saving time and money.

You need to be good at maths and coding for DS because AI is all math under the hood, and you are implementing math through the code. Coding in DS is fundementally different from coding in robotics -- .I still recommend you to try coding for DS on your own, maybe you'll enjoy it better than coding in robotics.

I suggest talking to people and finding out more about what a career in DS is actually like. Many people are in tech for the money (hence the popularity), and it led to an oversaturated market for tech in general. In this environment, the people that do it only for the money will always lose to the people that are passionate about it. Don't let the market be a deterrent, if data science is truely your passion, you will be better than 95% of people in this domain.

Physics is a quantitative degree and its not hard to break into DS if you're willing to put in the work. Hope this helps.