Most people likely cannot quit a high paying job when their identity is also wrapped in how much they’re earning. I see this a lot from all of the newly minted AI millionaires.
263 karma · joined May 13, 2015
"If the the average CIO is committing 10 or 15% of their budget to AI. If you're not in that you're getting shrunk."
I think just in general data engineer is a better term to find the same role across a lot of companies today.
Each job was scraped and then classified into a specific data science sub-group. We've also added filters for seniority, company, city, and more. We additionally added links to some job postings that have company interview guides that are on our site.
Hopefully this helps data scientists and alike find jobs that are relevant to their future job search!
2. Algorithm technical interviews provide a structure for companies to compare skill levels of different candidates against each other
3. Neither is the best scenario for either party but in a chaotic world without structure, each one is trying the best they can towards filling a job role by meeting with someone in a span of 45 minutes.
Personally as a founder of an interview prep company for data scientist (https://www.interviewquery.com/), I find that we try to just teach candidates concepts through bite-sized problems and repetition. Some people might hate it, but we're essentially playing the game that the companies are holding up. So you might as well learn to get good at it.
For example - I don't really drive that much on a day to day basis compared to the average American, and so if it's a huge 50% increase in gas prices yoy, that over indexes the inflation number for me because I might drive 80% less than the average American. So I would assume that inflation is really <7.9% for me.
We help data scientists land jobs by being the Leetcode for data science.
Youtube recommendation algorithm is so good at rewarding continuous creators. The difficulty is that the effort in making videos is surprisingly high and scaling is hard.
Am I missing something here?
What I want to know are which cities are great seasonal cities in which I could potentially buy a condo for the high seasons, and then leave in the non-high seasons for a potential rental at a still competitive price.
For example: SF sucks in the summer, but maybe the tourists don't know that.
It's pretty crazy how much a few words make a difference when it comes to people's inboxes getting pummeled with sales.
[1] https://www.interviewquery.com/blog-ab-testing-black-friday/
Maybe humans are getting better at treating what used to feel tough as relaxing. And if not, then society has to figure out how to deal with people that need to spend 95% of their day fishing or staring at a wall to function and be happy.
Ultimately these types of questions like "What is feature selection" are more likely to be encapsulated into case studies where the answer to the question itself will be, using feature selection.
For example: "Let's say you have thousands of categorical features for an anonymized dataset involving human traits, how would you figure out which predictors are the most important?"
Source: https://www.interviewquery.com/
Source: https://www.interviewquery.com/blog-do-they-want-a-data-scie...
Seems very probable that when it comes down to it and they had the pill in their hand, a lot would not go through with it once the reflection hits.