Asked repeated questions about previous company's metrics and internal information.
Data Scientist Interview Questions
Data Scientist Interview Questions
Lors d’un entretien pour le poste de data scientist, les employeurs vont poser des questions leur permettant d’évaluer vos compétences en modélisation des données, résolution des problèmes et programmation. Soyez préparé à répondre à des questions générales testant vos connaissances en statistiques et en science des données. Vous devez également être prêt à répondre à des questions ouvertes permettant de tester votre créativité, vos compétences en communication et votre éducation formelle en modélisation des données et en programmation.
Questions d'entretien d'embauche fréquentes pour un data scientist (H/F) et comment y répondre
Question 1 : Quelles techniques de modélisation des données préférez-vous et pourquoi ?
Question 2 : Comment détectez-vous les faux comptes Instagram utilisés pour escroquer les clients ?
Question 3 : Décrivez des situations qui requièrent une liste, un uplet ou un ensemble sur Python.
54,320 data scientist interview questions shared by candidates
Which of the 10 MBM Koch values do you identify with most strongly, and why? Tell us about a time you went above and beyond on a particular assignment or job duty. Tell us about a time you disagreed with your supervisor, etc.
What is the significance of p value.
Richiesta documentazione da compilare che ho compilato in parte in quanto non era chiaro come compilare...
Describe a statistical model you are using in your work now? (Referencing the model) explain the difference between random and fixed effects -- and what do they control for?
Hai mai avuto esperienze di fine tuning?
SQL question which required CTE
Write a social network that runs in memory. There should be four functions. makePost(userID, postID) follow(followerID, followedID) unfollow(followerID, followedID) showFeed(userID) The show feed function should show the posts made by the user, the posts made by the people the user followed and they should be in chronological order.
Standard questions about how I tackle business and data problems etc. However, as a data scientist I noticed one potentially red flag: the company is new and fresh in their data science department (although they have a solid data engineering and reporting base), but they want to start straight with GenAI/LLM stuff (Chat-GPT and whatnot). For those unfamiliar: it is pretty much a guaranteed pitfall as people would be using super-complex tools with zero knowledge of their inner workings (think of learning to run before you can walk).
At WRc there is a requirement to work on several projects at once, how would you effectively work to deliver high quality work to schedule?
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