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ML Knowledge
3 years ago
How do you tackle the issue of high cardinality within categorical data fields?
Data Scientist

Pinterest

Infineon

Calm

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3 years ago
Behavioral
3 years ago
If you receive an offer from Pinterest, how long do you think you'll stay here?
Data Scientist

Pinterest

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3 years ago
ML Knowledge
3 years ago
Could you walk me through the process of analyzing an ROC curve? How do bagging and boosting differ in reducing variance and bias?
Data ScientistMachine Learning Engineer

Pinterest

Zillow Logo

Zillow

Wish Logo

Wish

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3 years ago
ML Knowledge
3 years ago
Can you explain to me how cross-validation is applied in machine learning models, and what advantages it offers?
Data Scientist

Pinterest

ZocDoc Logo

ZocDoc

Binance Logo

Binance

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3 years ago
ML Knowledge
3 years ago
How would you distinguish batch normalisation from instance normalisation?
Data ScientistMachine Learning Engineer

Pinterest

eBay Logo

eBay

Samsara Logo

Samsara

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3 years ago
Behavioral
3 years ago
Tell me about a time where you showed ownership
Data ScientistTechnical Program ManagerSoftware EngineerProduct Manager

Pinterest

ApplyBoard Logo

ApplyBoard

Naspers Logo

Naspers

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3 years ago
Behavioral
3 years ago
How is your experience aligned with the values of Pinterest?
Data Scientist

Pinterest

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3 years ago
ML Knowledge
3 years ago
Can you please elaborate on how K-means and the Expectation-Maximization (EM) algorithm differ?
Data Scientist

Pinterest

Chewy Logo

Chewy

Wayfair Logo

Wayfair

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3 years ago
Data Visualization
3 years ago
How can you make multi-dimensional data comprehensible through visualization?
Data Scientist

Pinterest

Sprout Social Logo

Sprout Social

SwiftKey Logo

SwiftKey

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3 years ago
Behavioral
3 years ago
How did you handle a situation where you couldn't meet a deadline?
Data ScientistTechnical Program ManagerSoftware EngineerML Engineering Manager

Pinterest

Decathlon Logo

Decathlon

NVIDIA Logo

NVIDIA

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3 years ago

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*All interview questions are submitted by recent Pinterest Data Scientist candidates, labelled and categorized by Prepfully, and then published after being verified by Data Scientists at Pinterest.

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