[mturmon]

I'm a data science hiring manager. Other things besides just the raw academic credential (a PhD which wouldn't typically be in "Data Science" anyway, i.e., even the PhD's are just Data-Science-adjacent) are publications, conference appearances/posters, generated data products/pipelines, and contributions to relevant software. (For me, in that approximate order.)

I'd work on building some of those, because you do need to stand out against the field @MonteCarloHall described. (Software engineer + undergrad math/stats)

Those kind of achievements would satisfy screening filters. Then of course you'd have to have knowledge to back that up. I think it's reasonable to say that typically this will be domain-specific, e.g. you would end up with a different background knowledge base for NLP than for spatiotemporal problems than for network/graph problem domains. With all the growth has come specialization.

[listenallyall]

> the market is nowhere near saturation

Need to show > publications, conference appearances/posters, generated data products/pipelines, and contributions to relevant software.

These appear to be in conflict. If companies need people with such skills, they can't just hope to get the elite few who present at conferences, they need to be hiring among the audience members as well. If they are in fact just hiring the speakers, then the jobs aren't really "bountiful"

[mturmon]

> are publications AND/OR conference appearances/posters AND/OR generated data products/pipelines AND/OR contributions to relevant software. (For me, in that approximate order.)

^--- Taps sign

The above does not imply that I'd only consider conference speakers, right? (Although, there are a lot of conferences!) For some roles, contributions to relevant software would be the right standard.

[listenallyall]

I consolidated for brevity's sake, how could you not realize that. You are still talking about only considering the 1-3% (of conference speakers, article publishers, contributors to popular repos, pipeline generators) not the other 97-99% of audience members, article readers, users of those repos, pipeline consumers.

Is that clearer? Same exact point. Tap tap.