Ask HN: Is data science a dying profession?

https://news.ycombinator.com/item?id=34826587

by usgroup • 3 years ago

18 12 3 years ago

news.ycombinator.com

jstx14• 3 years ago

Not at all, why would it be?

wendyshu• 3 years ago

Increasingly a subskill of other positions, automated, or specialized.

jstx14• 3 years ago

The specialized part is kind of true to some extent but that's getting bogged down into job titles - data analyst, applied scientist, ML engineer, research scientist - some of these are used more often because "data scientist" is too broad and can mean a bunch of different things. But titles, schmitles - the point is that the skills are still very relevant.

And I'm not seeing anything getting automated.

usgroup2• 3 years ago

I think this is correct. So a DS does a bunch of stuff.

- Some of the stuff becomes diffused and common. Anyone can do it.

- Some of the stuff becomes data engineering.

- Some of the stuff becomes fitting a model -- anyone can do it.

- Some of the stuff ends up subsumed in a cloud providers offering and mostly automated.

- Some of the stuff becomes a SaaS (e.g. A/B testing).

Death by factorisation.

Specialisation is another sort of death, where X doesn't need a "Data scientist" any more, they need a "X data scientist". A bit like how "scientific computing" is just programming, except you wouldn't hire "just" programmers to do it -- you hire programmers who specialise in scientific computing.

sebastiansm• 3 years ago

I think is growing more than dying!

GianFabien• 3 years ago

My understanding is that data science implies big data.

As Jordan Tigani observes, there are not that many really big data situations[1].

Thus data science proficiency might be in support of business initiatives in a particular application domain and not a means to an end in itself.

[1] https://motherduck.com/blog/big-data-is-dead/

jstx14• 3 years ago

My understanding is that data science implies big data.

It really doesn't.

usgroup2• 3 years ago

I dont think OP is wrong -- the role popped up after 2007 Hadoop release. It was almost synonymous with running ML on big data and data scientists were typically computer science PhDs. It has become something quite different though. Now everyone and their dog is a data scientist.

palidanx• 3 years ago

so typically there are two sides of the house

1. data engineering - dealing with etl pipelines, data warehouses, data lakes, databases

2. data science - ai/ml, models etc

#1 preps things so #2 can do their jobs

alexmolas• 3 years ago

In my opinion, the term "Data Science" is becoming vague. Similar to the term "Web Developer" which lost its clarity in the 2000s and was divided into various roles like backend, frontend, UI, UX, app developers, and so on. Currently, "Data Science" has expanded and there are multiple subfields that have developed into their professions like data analyst, data engineer, machine learning engineer, machine learning scientist, and more. So in that sense yes, it's dying. But dying of success.

Ask HN: Is data science a dying profession?

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