[portal_narlish]

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.

[Fiahil]

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.

[kosei]

I think you're taking this analogy too literally.