Tech-Behavioral Mix

When assessing the performance of a machine learning model at Amazon, what evaluation metrics would you consider, and how do you ensure that the chosen metrics align with the business goals and requirements?

Business Intelligence Engineer

Amazon

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Behavioral
  • When assessing the performance of a machine learning model at Amazon, what evaluation metrics would you consider, and how do you ensure that the chosen metrics align with the business goals and requirements?
  • What metrics do you look at when evaluating an ML model for business decisions at Amazon?
  • How do you choose which performance metrics matter most for a specific BI use case?
  • Can you explain how you connect model metrics to real business goals?
  • In a BI scenario, how would you know if your ML model is doing its job well?
  • What's your approach to picking the right evaluation criteria when building models?
  • How do you measure the success of a machine learning model from a business impact perspective?
  • When reviewing a model's output, how do you decide whether precision, recall, or something else is more important?
  • Give an example where your choice of evaluation metric changed based on business context.
  • How do you handle situations where optimizing a model's accuracy doesn't align with business needs?
  • How do you communicate model performance in business terms to Amazon stakeholders?

Interview question asked to Business Intelligence Engineers interviewing at Amazon: When assessing the performance of a machine learning model at Amazon, what evaluation metrics would you consider, and how do you ensure that the chosen metrics align with the business goals and requirements?.