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Data Scientist Interview Questions

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Data Scientist Interview Questions

In un colloquio per Data scientist, ti verranno poste domande volte a verificare le tue capacità di data modeling, risoluzione di problemi e programmazione. Preparati a rispondere a domande di carattere generale che valutano la tua conoscenza della statistica e della scienza dei dati. Dovresti inoltre prepararti a rispondere a domande aperte mirate a testare la tua creatività, le tue doti comunicative e la tua formazione nella programmazione e modellazione dei dati.

Domande tipiche dei colloqui per Data scientist e come rispondere

Question 1

Domanda 1: Quali tecniche di data modeling preferisci e perché?

How to answer
Come rispondere: Trasformare i dati in informazioni comprensibili e fruibili è un aspetto fondamentale del lavoro di Data scientist. Con questa domanda i datori di lavoro vogliono capire il tuo backgruond e valutare le tue capacità di data modeling. Elenca e illustra le tecniche di data modeling che preferisci, includendo vantaggi come semplicità d'uso, flessibilità, ecc.
Question 2

Domanda 2: Come rilevi gli account Instagram fasulli utilizzati per raggirare i consumatori?

How to answer
Come rispondere: Domande come questa permettono ai selezionatori di testare le tue capacità di risolvere i problemi. Quando rispondi a domande aperte di questo tipo, non esitare a chiedere chiarimenti o a usare lavagne per dimostrare le tue abilità nel tracciare diagrammi e usare codici. Condividi il tuo processo di pensiero mentre elabori il problema.
Question 3

Domanda 3: Descrivi quali circostanze richiedono una lista, una tupla o un set in Python.

How to answer
Come rispondere: I selezionatori ti porranno domande come questa per testare le tue abilità di programmazione in Python. Ripassa gli elementi fondamentali di Python, come liste, tuple e set prima del colloquio. Dovrai essere in grado di spiegare quando e come ogni strumento deve essere usato da un Data scientist.

54,277 data scientist interview questions shared by candidates

We have two types of reviewers: careful reviewer (80% of reviewers) and lazy reviewers (20% of reviewers). Careful reviewers rate a post positive 60% of time and negative 40% of time). Lazy reviewers however rate a post positive 100% of time. A) what is the probability that a random ad is reviewed positively? B) If an ad gets a negative review, what is the probability that it's reviewed by a lazy reviewer? C) If 3 ads are reviewed positively in a row, what is the probability that they are reviewed by a lazy reviewer? D) Some as above with n positively reviewed ads in a row. What happens when n goes to infinity? E) If we have very few labeled data, how can we build a model to distinguish between careful and lazy reviewers?
avatar

Data Scientist, Analytics

Interviewed at Meta

3.5★
Mar 6, 2019

We have two types of reviewers: careful reviewer (80% of reviewers) and lazy reviewers (20% of reviewers). Careful reviewers rate a post positive 60% of time and negative 40% of time). Lazy reviewers however rate a post positive 100% of time. A) what is the probability that a random ad is reviewed positively? B) If an ad gets a negative review, what is the probability that it's reviewed by a lazy reviewer? C) If 3 ads are reviewed positively in a row, what is the probability that they are reviewed by a lazy reviewer? D) Some as above with n positively reviewed ads in a row. What happens when n goes to infinity? E) If we have very few labeled data, how can we build a model to distinguish between careful and lazy reviewers?

PLEASE DON'T TAKE THE PHONE SCREENING LIGHTLY! I did and got rejected. I was expecting SQL questions and in general talk about my resume but she asked me a question on product sense and I was completely unprepared for it. Creation of Facebook user groups has gone down by 20%, what will you do? sounds simple but I messed it up so badly. I was just blabbering anything in an unstructured way, I sounded so stupid and not even fit for a small company forget Facebook. The recruiter was nice and she did not say anything but I were to hear my own answer, I would reject myself on spot. I regret it so much wish I could have prepared for it. I hope someone sees this and it helps them. The SQL questions were easy and I did answer them correctly- what kind of joins to get only common rows, what the natural sorting order etc.
avatar

Data Scientist

Interviewed at Meta

3.5★
Mar 9, 2020

PLEASE DON'T TAKE THE PHONE SCREENING LIGHTLY! I did and got rejected. I was expecting SQL questions and in general talk about my resume but she asked me a question on product sense and I was completely unprepared for it. Creation of Facebook user groups has gone down by 20%, what will you do? sounds simple but I messed it up so badly. I was just blabbering anything in an unstructured way, I sounded so stupid and not even fit for a small company forget Facebook. The recruiter was nice and she did not say anything but I were to hear my own answer, I would reject myself on spot. I regret it so much wish I could have prepared for it. I hope someone sees this and it helps them. The SQL questions were easy and I did answer them correctly- what kind of joins to get only common rows, what the natural sorting order etc.

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