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Software Engineer (Data Science) Interview Experience

February 1, 2015
Neutral ExperienceNo Offer

Process

Campus interview first. Asked a lot of questions on machine learning, such as regularization, linear regression, and logistic regression.

Then a coding problem: Two-Sum (given an array and a target sum, find all the pairs that add up to the sum).

Phone interview as the second interview with the hiring manager.

Talked about the team and my skill set. Asked a bunch of questions about machine learning as well; most were concepts and definitions.

Then a coding problem: merge sort.

Questions

Linear Regression Model:

  • Define it.
  • How to get the least squares?
  • What is the difference between predictive data and real-world data?

What is a Logistic Regression Model?

  • Define it.
  • Give an example.

Do you know Bayes' Rule and Bayes' Theorem?

  • Give an example of using Bayes' Theorem.

Real-World Questions:

You have 1000 resumes in 10 classes. If you have a new resume, how can you classify it into the current classes?

What if there are no test cases for the model? How would you proceed?

What if the test sample is biased? What will you do?

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Workday's interview process for their Software Engineer (Data Science) roles in the United States is extremely selective, failing the vast majority of engineers.

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Candidates reported having mixed feelings for Workday's Software Engineer (Data Science) interview process in United States.

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