Tell me about a time you chose not to use machine learning, or chose a much simpler model, and why.

What the interviewer is looking for

• This question tests pragmatism & ownership. Chooses the simplest approach that meets the goal, owns outcomes in production and learns from what didn't work.
• What to bring out: Compares value, cost and risk, starts with a baseline, and is comfortable defending the simpler choice with results.
• Expect a follow-up like: What would have made you switch to a more complex approach?

Another way it may be asked: Think of a problem where rules or a basic model were the better answer. How did you decide that?

A structure to follow: STAR, with the weight on Action and Result

1. Step 1

   Situation

   One or two sentences: where, when and what was at stake. Pick a real example you were close to.

2. Step 2

   Task

   What you personally were responsible for. Say "I", not only "we", so the pragmatism & ownership you showed is visible.

3. Step 3

   Action

   The two or three things you did and why you chose them over the alternatives. This should be about half your answer.

4. Step 4

   Result

   What changed, in your own measure of it, and what you would do differently. Only use numbers you can stand behind.

This is guidance on shape, not a script. Use your own real experience and facts; never invent details to fill a gap. See the STAR guide and answer frameworks.

Common slips

• Describing what the team did without saying what you did.
• Choosing an example with no clear outcome, or one you cannot answer detailed questions about.
• Ending on the action and skipping the result and what you learned.

How to practise it

Write two bullet points for each STAR letter, then say the answer aloud in about two minutes.

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