Data scientist, programmer and software engineer are different things. They are not disjoint by any means, but this guy is conflating them in a way that's totally wrong.
Software engineers have to engineer things. They deal with production applications, distributed systems, concurrency, build systems, microservices... coding is sometimes only a small part of the job.
Data scientists nowadays do programming in interest of research, modeling and data visualization. But they are not only programmers - they are usually supposed to have an applied statistics or research background. Some also do software engineering, especially at companies serving data science/ML in their products.
A programmer is actually someone like a data analyst or business systems developer. They don't have to build systems themselves, they just write loosely structured code against existing systems. Like writing SQL queries for dashboards, or drop-in code for things like Salesforce. This is probably the closest thing to what he's describing as the "70s archetype". Minus the deep optimization stuff.
I agree with you. I've seen brilliant Data scientists struggling to understand how git branching works. But, as you say, their principal focus is applied statistics, not programming.
My role as a software engineer is to create a good enough architecture so their can use properly the information contained in their 60 GB CSVs.
As a side note, I also noticed that clients have no issue paying a lot for _Data Science_, but for the "software guys" ? That's a whole other story, despite being of equal importance to the project.
Software engineers have to engineer things. They deal with production applications, distributed systems, concurrency, build systems, microservices... coding is sometimes only a small part of the job.
Data scientists nowadays do programming in interest of research, modeling and data visualization. But they are not only programmers - they are usually supposed to have an applied statistics or research background. Some also do software engineering, especially at companies serving data science/ML in their products.
A programmer is actually someone like a data analyst or business systems developer. They don't have to build systems themselves, they just write loosely structured code against existing systems. Like writing SQL queries for dashboards, or drop-in code for things like Salesforce. This is probably the closest thing to what he's describing as the "70s archetype". Minus the deep optimization stuff.