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Thought this was interesting. Across 160 teams of researchers, just about all failed to make good life outcome predictions on things like GPA, evictions, layoffs, and others. Data followed 4.5k families across 15 years, with 13k features (varied over time). Haven't looked at it directly yet, but will be turning the docs and data inside out... In the meantime, authors claim this as showing the limits of ML. Oh, and it's published in PNAS, so you know there's some big publication energy there.
https://www.pnas.org/content/117/15/8398
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TBWA NY recruiter?
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TBWA NY recruiter?
Ok be honest, candidates. I really love this set of questions, I’ve been considering shifting my current interview style to these questions - I think they really give you an idea of who this person would be within the work setting. But the questions almost feel too deep for a recruiter to ask. What would you think if a recruiter took a different path and asked these questions instead of the usual ones?
https://blog.shrm.org/blog/9-interesting-interview-questions-that-actually-reveal-a-lot-about-candidat
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Most hiring managers look at patterns and context, not just the number of roles. A brief stint or two tied to layoffs, restructures, or account losses is usually fine if your story shows progression, solid references, and no unexplained exits, so use your resume and interviews to connect the dots and show stability despite the chaos
Also, any hiring manager worth their salt will know which agencies had layoffs. As long as your story matches reality you’re golden.