[jandrewrogers]

The base-level skill set is being a very good applied mathematician with some good computer science skills. This is why a lot of "data scientist" types have degrees in things like physics. A lot of the database ETL stuff can be learned.

This is the reason why I cannot be a "data scientist", despite being an expert in parallel algorithm design and with strong database ETL experience. It would require me spending a couple years studying mathematics in depth that I do not currently know. The vast majority of programmers are at least as deficient as I am in critical skills for these positions.

We train our data scientists at my company but we usually do not start with software engineers. Our feedstock is strong applied mathematicians with some programming skills because the mathematics part is by far the most difficult to train for someone who has not already been doing it for years.

[achompas]

This is the reason why I cannot be a "data scientist"

Are you worried about this outcome at all? Do you see yourself playing an important role on a data team, one with less modeling responsibilities but more infrastructure/DB responsibilities?

I'm considering this path and would love to hear your opinion.

[jandrewrogers]

To be clear, I chose this outcome. I am good with mathematics but not the mathematics usually needed as a data scientist and I have relatively little interest in investing the time to learn. Being a data scientist is a great job for some people but probably not what I would choose even if I was a developer again.

There is a continuum of skill balances; some people are more "data" than "scientist" and vice versa. The most useful balance varies from job to job. There are plenty of opportunities for people that have strong skills standing up clusters even if you have relatively weak analysis and model building skills. I would not dissuade anyone from becoming a data scientist, it will pay very well for the foreseeable future, but the skill set requires real effort to acquire. At a small company there is likely opportunity to learn the trade by coming at it from the infrastructure side of things.

It is a young enough area that it should be pretty easy for talented individuals to invent a career if they apply themselves.

[achompas]

Thanks for the excellent summary. This line:

I am good with mathematics but not the mathematics usually needed as a data scientist

resonates with me. If you're thinking of data science, you're facing a loooooong road of coursework (scientific computing or numerical methods, linear algebra, PGMs, machine learning, AI, possibly some optimization too) to get your foot in the door. I'm going to try, but one could spend years finishing that work.

In some ways, getting a data science gig is the opposite of getting a web developer gig. In DS you're competing with a large supply of intelligent PhDs, so credentials are very important; for web dev, your portfolio goes much further than any credentials.