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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.

54,292 data scientist interview questions shared by candidates

0) Tell about your current job and work experience. I) Conditional probability dice questions: a) Expected pay-off of a single roll single dice game (Entry fee $3). The amount the player gets is the face value of the dice. Ans: $3.5 - $3 = $0.5 b) Expected pay-off of a double roll single dice game(entry fee $4). Rule: the player can either hold or continue the game after the first roll. If the player continues the player forfeits the money received after the first round.Ans. $4.25(Expected values check stack overflow for the math) - $4 = $0.25 c) Which of a) or b) has a higher payoff. Ans. obviously game (a). 2) The probability of watching at least one star in 1 hr = 0.64. What is the probability of watching at one start in 30 mins? Ans. 0.4 (Again search StackOverflow) 3) What kind of casino machine would you recommend based on two options knowing that patrons play option B longer but the casino earns slightly less per hour from the machine than option A?
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Data Scientist

Interviewed at Clover Health

3.6★
Aug 24, 2021

0) Tell about your current job and work experience. I) Conditional probability dice questions: a) Expected pay-off of a single roll single dice game (Entry fee $3). The amount the player gets is the face value of the dice. Ans: $3.5 - $3 = $0.5 b) Expected pay-off of a double roll single dice game(entry fee $4). Rule: the player can either hold or continue the game after the first roll. If the player continues the player forfeits the money received after the first round.Ans. $4.25(Expected values check stack overflow for the math) - $4 = $0.25 c) Which of a) or b) has a higher payoff. Ans. obviously game (a). 2) The probability of watching at least one star in 1 hr = 0.64. What is the probability of watching at one start in 30 mins? Ans. 0.4 (Again search StackOverflow) 3) What kind of casino machine would you recommend based on two options knowing that patrons play option B longer but the casino earns slightly less per hour from the machine than option A?

Without going into detail, they wanted both Python code for transforming raw data into data in some form from which one could make predictions, as well as a written description of what was done, why, and the modeling approach one would take.
avatar

Data Scientist

Interviewed at DICK'S Sporting Goods

3.8★
Feb 18, 2022

Without going into detail, they wanted both Python code for transforming raw data into data in some form from which one could make predictions, as well as a written description of what was done, why, and the modeling approach one would take.

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