Not to be a dick, but what kind of research role do you expect to get without strong stats knowledge? Any worthwhile “research” job-title carries that assumption. It may be a bummer but what good is research if it can’t be quantified? (Especially to the business paying you to do it).
Any research job will also require basic (at the minimum) data skills, so it’s well worth the effort to brush those up.
I work as an applied scientist in faang. First role was on a team doing machine learning research. Have since transitioned to a team where my work is more focused on writing software. Love it. Good pay. WLB. Work often more satisfying than skating these days.
I'm going to push back on this for a few reasons:
1) The some of the biggest insights in the social sciences came from ethnographers, those who do interviews, and those who conduct experiments.
I think it is rather arrogant to dismiss the work of Goffman, Wacquant, the Adlers (despite their ethical issues), Milgram (different ethical issues), Gottdiener, and others who have done brilliant work and reframed the way we see the world.
2) Simply running regressions without any theoretical underpinnings leads to superficial results with little meaning. Fancy equations allow bad results to adorn themselves in the Emperor's New Clothes. "What you can't see how brilliant this is because of how complex my regression is?"
3) Those who have done the best research on skateboarders (Becky Beal, Ian Borden, and Ocean Howell) were all qualitative researchers. A data scientist just running the numbers on some skateboarders could very easily lead to superficial understandings of skaters... and maybe this is part of the reason there is yet to be a stand out quant study on skaters.
Finally, I think the the qual vs quant battle is rather silly, instead the two forms of research build upon one another. This is the first time I've ever had anyone approach me and say, "No research but quant research has value."
Dismissing the disciplines of anthropology, sociology, communications, social-psych, psych, the qual side of UX research (if we want to pretend UX is a discipline), because only crunching numbers has value comes off as rather offensive and arrogant.