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ML CaseProduct Case

2 years ago

What architecture would you propose for a recommendation engine that adapts to a user's musical preferences, and how would you integrate their listening traits?

Data Scientist

Workday

Productboard

Shopee

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2 years ago

Statistics

2 years ago

What is your grasp of the difference between the frequentist and Bayesian approaches to probability? Also, when faced with a decision of which method to use, what indicators would you factor in?

Data Scientist

Workday

Noom

Bloomberg

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2 years ago

Behavioral

2 years ago

Please tell us about a time when you did not reach your goal.

Data ScientistData Engineering ManagerUX DesignerEngineering Manager

Workday

Chewy

SAP

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2 years ago

Statistics

2 years ago

How can you describe Markov Chains to make them clear to a non-expert?

Data Scientist

Workday

Yelp

Skyscanner

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2 years ago

ML Knowledge

2 years ago

What role does Gradient Descent play in the development and training of deep learning models?

Data Scientist

Workday

Booking.com

BetterUp

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2 years ago

Behavioral

2 years ago

Describe a time when you disagreed with a team member's approach.

Data ScientistTechnical Program ManagerSoftware EngineerProduct Manager

Workday

Lenskart

Takeaway

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2 years ago

ML CaseML Knowledge

2 years ago

How does the R-square measure fall short in providing a complete picture of linear regression model performance? What does it imply about the linear regression model when you encounter a low R-square?

Data Scientist

Workday

Bloomberg

HubSpot

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2 years ago

ML CaseML Knowledge

3 years ago

What steps would you follow to estimate Pi using the Monte Carlo Algorithm?

Data ScientistMachine Learning Engineer

Workday

Grafana Labs

Chewy

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3 years ago

Behavioral

3 years ago

Describe a time when you went above and beyond the call of duty

Data ScientistProgram ManagerFrontend EngineerFull Stack Software Engineer

Workday

Figma

Duolingo

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3 years ago

ML Knowledge

3 years ago

When we talk about decision trees, how do we consider bias and variance? And, if you wouldn't mind, which do you think is more challenging: high bias or high variance, and give us an explanation for that assertion?

Data Scientist

Workday

Elastic

Rivian

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3 years ago

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

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