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> I’d rather work on a project that builds something and the effort accumulates into something more tangible than an analysis report. There are data science jo
by jstx1 4y ago
> I’d rather work on a project that builds something and the effort accumulates into something more tangible than an analysis report.
There are data science jobs in which your output is at most a report, and there are data science jobs in which you're responsible for ML experiments, prototyping, building and maintaining services, model deployment etc. Sometimes that's called ML engineer but a lot of the time it's data scientist too (which title is used more kind of varies by country too from what I've seen).
You might like the second type of DS job more, or if you already have that kind of job then switching to SWE is easier because you're basically already a SWE and you're just switching domains instead of breaking into SWE.
- agnosticmantis 4y agoThanks for the detailed answer. I’ve actually been thinking about ML engineering too for exactly the reason you said. Are there any books/resources that you’d recommend for such a transition?
- apohn 4y agoI've also seen a new title called "Applied Scientist." I think at a particualar FAANG company (I don't remember which one), Data Scientist = Insights+Reports, Applied Scientist = Building Data Pipelines+Models, and ML Engineer = Take data pipelines+models built by others and put it in production, meeting SLAs, costs, etc. For good reason, most companies don't specialize to that degree. As you've pointed out, the titles vary across company and/or geography, so the best thing to do is ask the recruiter or hiring manger what is expected of the role.