[SatvikBeri]

I think the "Data Scientist" job title is overloaded–I see several clusters of skills being useful, and in my ideal world they would have similar but slightly different job titles:

–Medium Stats/ML, medium Engineering ("Data Scientist" or "Data Engineer")

–High Engineering on very large datasets, low/medium Stats/ML ("Data Engineer" or "Backend Engineer")

–High Analysis, medium Stats/ML, low Engineering ("Analyst")

–High traditional Stats, High Analysis, low ML/Engineering ("Statistician")

–High ML, medium Stats, medium Analysis ("Data Scientist")

–High ML, medium Engineering ("Machine Learning Engineer")

[tangue]

One of the lessons of the web (in the 1990s everyone was a webmaster until the field mature.) is that after the coders, specialists emerged in fields like design, management, UX, seo and content. For data science the most obvious is data visualization but I guess there's plenty of new jobs ahead in addition to core data science jobs.

[di4na]

the second most obvious is cleaner. 90% of time spent when i try to do any analysis is just spent trying to get data that are usable, or in an usable shape.

And let's not talk about the different CSV you can encounter... or how to get data out of databases that are literally the only reason some "guardian DBA" still have a job. It can take months to get any access, if you ever get it...