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Data Scientist Interview Questions

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Data Scientist Interview Questions

In een sollicitatiegesprek voor de functie data scientist (M/V/X) kunt u verwachten dat de werkgever vragen stelt die uw vaardigheden voor gegevensmodellering, probleemoplossing en programmeren onderzoeken. Wees voorbereid op algemene vragen die uw kennis van statistiek en data science. Stel u ook in op open vragen die uw creativiteit, sociale vaardigheden en formele opleiding in gegevensmodellering en programmeren testen.

Meest gestelde sollicitatievragen voor een data scientist (M/V/X) en hoe te antwoorden

Question 1

Vraag 1: Welke gegevensmodelleertechnieken hebben uw voorkeur en waarom?

How to answer
Zo antwoordt u: Gegevens vertalen naar begrijpelijke en bruikbare informatie, is een essentieel onderdeel van de rol van een data scientist. Met deze vraag kunnen werkgevers uw gegevensmodelleringsvaardigheden en achtergrond doorgronden. Noem de voor u preferente gegevensmodelleringstechnieken en bespreek deze, bijvoorbeeld voordelen als gebruiksgemak, flexibiliteit, etc.
Question 2

Vraag 2: Hoe zou u nepaccounts op Instagram detecteren die gebruikt worden om consumenten op te lichten?

How to answer
Zo antwoordt u: Met zulke vragen kan een werkgever uw probleemoplossend vermogen testen. Bij het beantwoorden van open vragen als deze, is het prima om zelf naar verduidelijking te vragen en een whiteboard te gebruiken om te laten zien dat u kunt programmeren en dat u diagrammen kunt maken. Deel uw gedachtegang terwijl u de stappen van het probleem behandelt.
Question 3

Vraag 3: Beschrijf omstandigheden die een lijst, tupel of set in Python vereisen.

How to answer
Zo antwoordt u: Vraagstellers gebruiken dergelijke vragen om uw kennis van de programmeertaal Python te testen. Ga voor het sollicitatiegesprek de grondbeginselen van Python, zoals lijsten, tupels en sets. U zou moeten kunnen uitleggen wanneer en hoe elke tool door data scientists wordt gebruikt.

54,327 data scientist interview questions shared by candidates

business sense: There are two types of cars A and B. The number of people in US who use A and B are the same. They drive the same distances each month. Now there are two new technologies, X and Y (of equal cost). If apply X, mpg of A would increase from 50 mpg to 75 mpg; If apply Y, mpg of B would increase from 10 mpg to 11 mpg. The goal is to decrease the dependence on foreign oil, or to decrease the consumption of gasoline. Question: which technology would you apply? Follow up question: after applying the technology of your choice, assume there's money available for research on new technology, which car would you choose to conduct research on?
avatar

Data Scientist

Interviewed at Meta

3.5★
Jan 7, 2015

business sense: There are two types of cars A and B. The number of people in US who use A and B are the same. They drive the same distances each month. Now there are two new technologies, X and Y (of equal cost). If apply X, mpg of A would increase from 50 mpg to 75 mpg; If apply Y, mpg of B would increase from 10 mpg to 11 mpg. The goal is to decrease the dependence on foreign oil, or to decrease the consumption of gasoline. Question: which technology would you apply? Follow up question: after applying the technology of your choice, assume there's money available for research on new technology, which car would you choose to conduct research on?

SQL part1 Question # 1 : you have the following table - User_id , action (post, edit, cancel) , date == > what is the post rate Question # 2 : you have also the following table (active users) - User_id , country , active , date == > What is the average post rate for yesterday for all active users by country
avatar

Data Scientist

Interviewed at Meta

3.5★
Aug 7, 2019

SQL part1 Question # 1 : you have the following table - User_id , action (post, edit, cancel) , date == > what is the post rate Question # 2 : you have also the following table (active users) - User_id , country , active , date == > What is the average post rate for yesterday for all active users by country

Lets say the population on Facebook clicks ads with a click-through-rate of P. We select a sample of size N and examine the sample's conversion rate, denoted by hat{P}, what is the minimum sample size N such that Probability( ABS(hat{P} - P) < DELTA ) = 95%. In other words (this is my translation), find the minimum sample size N such that our sample estimate hat{P} is within DELTA of the true click through rate P, with 95% confidence.
avatar

Data Scientist, Analytics

Interviewed at Meta

3.5★
Mar 6, 2015

Lets say the population on Facebook clicks ads with a click-through-rate of P. We select a sample of size N and examine the sample's conversion rate, denoted by hat{P}, what is the minimum sample size N such that Probability( ABS(hat{P} - P) < DELTA ) = 95%. In other words (this is my translation), find the minimum sample size N such that our sample estimate hat{P} is within DELTA of the true click through rate P, with 95% confidence.

Given two binary strings, write a function that adds them. You are not allowed to use any built in string to int conversions or parsing tools. E.g. Given "100" and "111" you should return "1011". What is the time and space complexity of your algorithm?
avatar

Data Scientist, Analytics

Interviewed at Meta

3.5★
Mar 6, 2015

Given two binary strings, write a function that adds them. You are not allowed to use any built in string to int conversions or parsing tools. E.g. Given "100" and "111" you should return "1011". What is the time and space complexity of your algorithm?

We have a table called ad_accounts(account_id, date, status). Status can be active/closed/fraud. A) what percent of active accounts are fraud? B) How many accounts became fraud today for the first time? C) What would be the financial impact of letting fraud accounts become active (how would you approach this question)?
avatar

Data Scientist, Analytics

Interviewed at Meta

3.5★
Mar 6, 2019

We have a table called ad_accounts(account_id, date, status). Status can be active/closed/fraud. A) what percent of active accounts are fraud? B) How many accounts became fraud today for the first time? C) What would be the financial impact of letting fraud accounts become active (how would you approach this question)?

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