In einem Vorstellungsgespräch für Datenwissenschaftler stellen Arbeitgeber wahrscheinlich Fragen zur Beurteilung Ihrer Kompetenzen in Datenmodellierung, Problemlösung und Programmierung. Bereiten Sie sich darauf vor, allgemeine Fragen zu beantworten, die Ihre Kenntnisse in Statistik und Datenwissenschaft testen sollen. Sie müssen evtl. auch offene Fragen beantworten, mit denen Ihre Kreativität, Kommunikationsfähigkeiten und Ihre Ausbildung in Datenmodellierung und Programmierung geprüft werden.
Building a histogram of post reply count in SQL (number of posts with x replies, x+1 replies, etc). Building a table with a summary of feature usage per user every day (keep track of the last action by user and roll that up every day). Basic conditional probabilities (check out brilliant.org for their source of inspiration)
Flip one coin 10 times and obtain one H, what is the p value and null hypothesis?
You randomly draw a coin from 100 coins - 1 unfair coin (head-head), 99 fair coins (head-tail) and roll it 10 times. If the result is 10 heads, whats the probability that the coin is unfair?
As a part of a bigger question: "How do you draw a uniform random sample from a circle in polar coordinates?"
If you give N riders with the probability of P a $5 coupon, what is the expected coupon spend
What was the angle between the clock hands at 3:15.
You have a google app and you make a change. How do you test if a metric has increased or not?
How would you measure the health of Mentions, Facebook's app for celebrities? How can FB determine if it's worth it to keep using it? If a celebrity starts to use Mentions and begins interacting with their fans more, what part of the increase can be attributed to a celebrity using Mentions, and what part is just a celebrity wanting to get more involved in fan engagement?
Case Interview: the case is the car finance loan. - what are revenues and expenses - given a model that predicts when a customer is good (loan should be approved) or bad (loadn should be decline) find out: 1. the probability that the customer is good given the model predicts good 2. the probability that the customer is bad given the model is good 3. given a pentile graph of # of checked off loans / # of loans what is a better model than the current; what is the best model. Behavioral interview: - tell me about a time that you had to deal with changing objectives in your team/project - tell me about a time that you had to deal with unexpected problems in your project - tell me about a time that you had to persuase somebody Role interview: the case is a report on air company with low percentage of flight on time. Read the report an give an evaluation of it and some reccomendations to your boss. 15 minutes to read the report and remove anything unecessary or spot errors. 20 minutes to present it to your boss. 15 minutes to discuss afterwards from data scientist to data scientist.
A set of values given: Assume table in SQL or list of dictionaries if using Python. Basically a row of data contained information: if it is post or it is a comment, row id and some other data. Find distribution of comments. #comments # posts 1 5000 2 6787 .. ..
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