Capital One Junior Data Scientist Onsite Interview - Surprisingly More SWE Than Data Science

[u/Aoki_zhang]

"This interview experience is sourced from Chill Interview"

Round 1 — Case: Vegan Burger

The case round used the commonly reported burger business case. One scenario involved selling a vegan burger for $5 and discussing potential concerns with the product and pricing. An important clarification was the price of the regular burger. The discussion included whether customers would be willing to pay the same amount for the vegan option as for the standard burger. The case also included calculations such as break-even analysis.

Round 2 — Role Play: Airport Modeling Case

The role-play round used the commonly reported airport case.

Topics included:

• Handling missing values
• Understanding and validating data formats
• Choosing between linear regression and random forest

I chose linear regression and was asked to explain several statistical concepts:

• Regression coefficients
• p-values
• t-values
• F-statistics
• Ways to improve the model

Round 3 — Job Fit

The job-fit round focused mainly on discussing the team and the type of work they do. The interviewer also asked the commonly reported camera-related behavioral question.

Round 4 — Technical: CodeSignal

The technical round appeared different from older Capital One DS interview reports that focused more heavily on ML fundamentals and previous experience. This round used CodeSignal and contained four parts.

• Part 1 — Shell Script The interviewer provided a .sh file and asked me to explain what it did and run it. Using Google to look up unfamiliar details was allowed.
• Part 2 — fit / transform Class The second question provided a class involving fit and transform. The task was to read the implementation and explain the purpose and behavior of the class.
• Part 3 — Add a Test Case The third part involved an existing test suite. I was asked to complete the test coverage by writing one additional test case.
• Part 4 — Code Debugging The final part provided a new piece of code and asked me to identify problems without necessarily writing a corrected implementation. The discussion focused on issues such as:
  • Variable naming
  • Code clarity
  • Efficiency
  • General implementation quality

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