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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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Do you have experience as a data scientist?
kaggle projects using different tools/tech stacks, PySpark, Python, R and whatever ML algorithms you implement for whatever business case you solve
Clearly express the business value of your model
Why do you want to become a data scientist? When hiring data scientists all I work for is substantial experience and in depth understanding of tools, technology, and various languages. Most people either bold these in line or provide summary
Visual Storyteller
So as a manager of a few teams including DS - I would look up REQs for data scientists (happy to share a couple I’ve put out) and align accordingly. I mainly look for software/tech stack skills, languages, education, certs, and projects where you’ve operated in a team environment driving innovations.
Talk specifically about the tools you've used. Not just that you did a thing, but what languages and packages.
Guess an outstanding academic experience (mostly graduate degree) is required?