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Robinhood Data Scientist Mock Interview

Question 2 of 30 for our Robinhood Data Scientist Mock Interview

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Question 2 of 30

Can you define cross-validation and describe how you use this process when analyzing a data set?

"As a data scientist here at Robinhood, I would use cross-validation to assess how well the analysis model I am using will perform on a new and independent dataset. A typical way to use cross-validation is to split the data into two sets. You then use one data set to build the model and the second one to test your analysis. This helps to improve the accuracy of and my trust in the results of the analysis."

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How to Answer: Can you define cross-validation and describe how you use this process when analyzing a data set?

Advice and answer examples written specifically for a Robinhood job interview.

  • 2. Can you define cross-validation and describe how you use this process when analyzing a data set?

      How to Answer

      This is a technical question asking for both the definition of the term and an explanation of how you would use it in your work as a data scientist if hired by Robinhood. During an interview, you should make sure you always listen carefully to the complete question. Many candidates will begin formulating their answers as soon as the interviewer begins asking the question. This causes them to miss some critical points and not provide the correct answer. A useful technique to counter this is to pause for two seconds before beginning to answer the interviewer's question. This also ensures you will not 'step on' the Robinhood interviewer when they are still talking, which is a critical mistake during an interview.

      Answer Example

      "As a data scientist here at Robinhood, I would use cross-validation to assess how well the analysis model I am using will perform on a new and independent dataset. A typical way to use cross-validation is to split the data into two sets. You then use one data set to build the model and the second one to test your analysis. This helps to improve the accuracy of and my trust in the results of the analysis."