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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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The hiring bar at good tech companies is quite high, so you need an intermediate landing zone first where you can learn and implement new stuff. Such companies are willing to take a chance with you if you have got decent knowledge and some hot certifications. You may have to take a pay cut as well if the learning potential is high. People call these positions — ‘catapult’ roles.
Been there, done that. Started from an IT sweatshop. Now joining Databricks after spending some time in a catapult role. Good luck.
I would define a good catapult company or role as the one which has the tech exposure and learning curve ideal for you to make a major leap in future. Hypothetically say, ‘If I work in this role for 1.5 years, I will get the knowledge and skills equivalent to 4 years elsewhere’. That has been my philosophy. It could vary for others.
F
Hey - what’s your education? What’s your plan to upskill?
I’d jump in as analyst at tech then move over.
Will be easier and more $$ than trying to go Data Eng / DS at non tech then switching to same role in Tech.
I have a BS in Data Science
I’m going over all the courses in R to brush up and taking some coursera certificates in Python Data science too