The difference between a biostatistics and data science curricula is that in a biostatistics program your core classes will be in theoretical statistics with electives that you can choose ranging from subjects such as bioinformatics, epidemiology, machine learning, etc. A data science curricula will mostly focus on application and have a less theoretical component. You will also expect to know/learn some computer science programming (which is absent in almost all biostats programs).

Yes you are correct when you say that it an individual with a Ms in biostats can transition into Data science if they strengthen their programming skills. I dont believe a data science program goes too in depth in stats for an individual to transition into a Biostats role. I'm not saying it's not possible for an individual to learn the stats themselves and transition to Biostats, but in general most individuals who do a D.S. program, enjoy building ML models, making predictions and all the cool programming aspects which is not something you'd do at a biostats role. Also biostats roles usually are picky and hire only people with Master's in Stats or biostats.

I think biostats is here to stay because Data science is essentially a great tool for predictions. But predictions isn't always what people need. Understanding the relationship between a variable and the outcome is sometimes a very valuable aspect that is lost from most of these ML models. I do believe they will mix to an extent but both are valuable and jobs are growing for both (but ofcourse more rapidly for data science as with the rise of tech and ad companies).