I think most people do, but I've never heard a good term for the job. It's like "we want someone who can take large amounts of data and do something awesome with it". What do you call that?
>Unless you're hiring someone really junior, you want the "data scientist" to have a specialty -- anyone good will have one.
Not sure I agree with this, I want people who are well-rounded. I think it's great to find someone who specialized at something, but I'd want that person to be able to grow the rest of his abilities up to par. Example: let's say you specialized in machine learning. If you don't understand building scalable systems, you can't take a holistic view of a project; how will you know if your algorithms can scale to a production environment? Or, if you can't program well, you can't write code to actually get your algorithms into place. Or if you can't understand the business side of things, you won't be able to build trust with the rest of the company, and hence you won't be able to contribute.
That's close to what I used to be called. It's a very overused and vague term, I'd argue far worse than the already bad 'data scientist'. Search job postings for 'analyst' and see the wide variety of jobs that turn up.
>"we want someone who can take large amounts of data and do something awesome with it"
Yeah, that's kind of the problem; until "awesome" gets defined, it's awfully hard to be specific about what the company needs. But this is why it's going to be really hard for someone that couldn't do part of the job themselves to hire effectively.
As to the second point, I guess it's going to depend on the business and on whether the statistical component is crucial or just peripheral. It's nice if everyone is pretty broadly well trained. But if you're a hedge fund building algorithmic trading rules, you need different people than a marketing research firm or a litigation consulting agency.
I think most people do, but I've never heard a good term for the job. It's like "we want someone who can take large amounts of data and do something awesome with it". What do you call that?
>Unless you're hiring someone really junior, you want the "data scientist" to have a specialty -- anyone good will have one.
Not sure I agree with this, I want people who are well-rounded. I think it's great to find someone who specialized at something, but I'd want that person to be able to grow the rest of his abilities up to par. Example: let's say you specialized in machine learning. If you don't understand building scalable systems, you can't take a holistic view of a project; how will you know if your algorithms can scale to a production environment? Or, if you can't program well, you can't write code to actually get your algorithms into place. Or if you can't understand the business side of things, you won't be able to build trust with the rest of the company, and hence you won't be able to contribute.