Can you explain how this algorithm works? Estimate the cross-sell potential for this client. Take me through one of your projects.
Datenwissenschaftler Interview Questions
Datenwissenschaftler Interview Questions
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.
Typische Bewerbungsfragen als Datenwissenschaftler (m/w/d) und wie Sie diese beantworten
Frage 1: Welche Verfahren der Datenmodellierung bevorzugen Sie und warum?
Frage 2: Wie würden Sie gefälschte Instagram-Konten feststellen, mit denen Verbraucher betrogen werden sollen?
Frage 3: Beschreiben Sie Umstände, die in Python eine Liste, ein Tuple oder Set erfordern.
33,531 datenwissenschaftler interview questions shared by candidates
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 .. ..
very easy questions and took very less time
One time you had disagreement with supervisor
R4: Assume the distribution of children per family is given by: # children 0 | 1 | 2 | 3 | 4 | >=5 p 0.3 | 0.25 | 0.2 | 0.15 | 0.1 | 0 Consider a random girl in the population of children. What's the probability that she has a sister?
Tell me about yourself and your experience
Tell me about a time when you took a risk
SQL: there is a table of time,post id, action and content. the action can be reported and the content is spam. another table of time,post id, user - of all posts were removed manually the question: What percent of yesterday's content views were on content that has been reported for spam and removed yesterday?
Why Facebook? What is probability of pulling a different color or shape card from a shuttled deck of 52 cards? A business sense question on how to improve a service and a sql query question given a table.
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