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Datenwissenschaftler Interview Questions

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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

Question 1

Frage 1: Welche Verfahren der Datenmodellierung bevorzugen Sie und warum?

How to answer
So beantworten Sie die Frage: Daten in verständliche und aktionsfähige Informationen umzuwandeln ist ein kritischer Bestandteil der Arbeit eines Datenwissenschaftlers. Mit dieser Frage können Arbeitgeber Ihre Fähigkeiten in Datenmodellierung und Ihren Hintergrund in Erfahrung bringen. Führen Sie Ihre bevorzugten Datenmodellierungstechniken auf und erläutern Sie die jeweiligen Vorteile wie einfache Anwendung, Flexibilität usw.
Question 2

Frage 2: Wie würden Sie gefälschte Instagram-Konten feststellen, mit denen Verbraucher betrogen werden sollen?

How to answer
So beantworten Sie die Frage: Mithilfe von Fragen wie dieser kann ein Arbeitgeber Ihre Problemlösungskompetenz prüfen. Bei der Beantwortung offener Fragen wie dieser können Sie ruhig klärende Fragen stellen und Whiteboards verwenden, um Ihre Programmier- und Diagrammfähigkeiten vorzuführen. Verdeutlichen Sie Ihren Denkprozess bei der Behebung des Problems.
Question 3

Frage 3: Beschreiben Sie Umstände, die in Python eine Liste, ein Tuple oder Set erfordern.

How to answer
So beantworten Sie die Frage: Personalverantwortliche verwenden Fragen wie diese, um Ihre Python-Programmierkenntnisse zu prüfen. Gehen Sie vor dem Vorstellungsgespräch die Grundlagen von Python wie Listen, Tuples und Sets durch. Sie sollten erklären können, wann und wie jedes Tool von Datenwissenschaftlern eingesetzt wird.

33,633 datenwissenschaftler interview questions shared by candidates

Tech Interview had 2 parts: 1.) 2 SQL questions very easy - based on a join of couple of tables and group by. 2.) Product sense: - What could go bad and good in 10% increase in clicks on Events via Facebook Search? - Having several backend external feeds like twitter, YouTube, etc., in Facebook search can cause what to go right and what to go wrong?
avatar

Data Scientist, Analytics

Interviewed at Meta

3.5★
Jul 13, 2021

Tech Interview had 2 parts: 1.) 2 SQL questions very easy - based on a join of couple of tables and group by. 2.) Product sense: - What could go bad and good in 10% increase in clicks on Events via Facebook Search? - Having several backend external feeds like twitter, YouTube, etc., in Facebook search can cause what to go right and what to go wrong?

In order to push existing users to refer their friends, we're running a special reward program, in which the user is given an instant $10 discount for posting a referral message as their Facebook status. The message looks something like this: "Check out this company Jerry.ai --they automatically checks if you’re paying the lowest price for insurance and they will also find the best quote for you. As a friend of mine, you can get $20 off your insurance purchase. Click here to get the $20 gift credit: jerry.ai " The user is given the option to post this message on his/her Facebook account during the purchase. Once they post this message, they instantly get the $10 discount on their purchase. In other words, we don't wait for any of their referred friends to actually signup with us before giving them the discount. We feel that doing this would make the users more likely to post the referral message. Assume that this reward program has been running for a couple of months, and we have some data collected in our database. We want to know if running this program has been a good idea or not, i.e., are we acquiring new customers with it, or are we just losing money by giving out $10 discounts. Assume that you have the following database tables: 'User' and Purchase' Table User id, name, referring_user_id Table Purchase id, user_id, date, total, discounts In the Purchase table, the 'total' field contains the dollar amount of the job. The 'discounts' field consists of the total discounts given for the appointment (including rewards, coupon redemptions, etc.). Therefore, the customer pays: 'total' - 'discounts' as their final bill. Given this data: 1) 'What' information would you derive from it, and 'how' will you derive it (you can give SQL queries, pseudo code, ... whatever you're comfortable with) 2) Using the information from Step 1), how would you make a recommendation on whether this rewards program should be continued or discontinued
avatar

Data Scientist

Interviewed at Jerry

4.1★
Apr 27, 2021

In order to push existing users to refer their friends, we're running a special reward program, in which the user is given an instant $10 discount for posting a referral message as their Facebook status. The message looks something like this: "Check out this company Jerry.ai --they automatically checks if you’re paying the lowest price for insurance and they will also find the best quote for you. As a friend of mine, you can get $20 off your insurance purchase. Click here to get the $20 gift credit: jerry.ai " The user is given the option to post this message on his/her Facebook account during the purchase. Once they post this message, they instantly get the $10 discount on their purchase. In other words, we don't wait for any of their referred friends to actually signup with us before giving them the discount. We feel that doing this would make the users more likely to post the referral message. Assume that this reward program has been running for a couple of months, and we have some data collected in our database. We want to know if running this program has been a good idea or not, i.e., are we acquiring new customers with it, or are we just losing money by giving out $10 discounts. Assume that you have the following database tables: 'User' and Purchase' Table User id, name, referring_user_id Table Purchase id, user_id, date, total, discounts In the Purchase table, the 'total' field contains the dollar amount of the job. The 'discounts' field consists of the total discounts given for the appointment (including rewards, coupon redemptions, etc.). Therefore, the customer pays: 'total' - 'discounts' as their final bill. Given this data: 1) 'What' information would you derive from it, and 'how' will you derive it (you can give SQL queries, pseudo code, ... whatever you're comfortable with) 2) Using the information from Step 1), how would you make a recommendation on whether this rewards program should be continued or discontinued

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