The 60-second answer
Start with the business cost of false positives and false negatives and choose metrics such as precision, recall, PR-AUC, or cost-weighted utility. Use stratified splits and inspect per-class/slice performance; accuracy alone is usually misleading.
Build the answer in this order
Start with the business cost of false positives and false negatives and choose metrics such as precision, recall, PR-AUC, or cost-weighted utility.
Use stratified splits and inspect per-class/slice performance; accuracy alone is usually misleading.
Training options include class weights, focal-style losses, under/oversampling, and threshold tuning.
Calibrate probabilities and select an operating threshold on validation data that matches the product objective.
A useful interview mental model
This is the shape of a strong answer—not a script to memorize.
Senior-level signal
- Account for prior/prevalence shift between training and production because it can change precision and calibration.
- Monitor rare-class recall and alert volumes separately so operational capacity is part of the decision.
What the interviewer is really testing
Likely follow-up questions
Common weak-answer patterns
- Reciting a definition without mechanism or assumptions.
- Claiming one technique is always better without a data regime.
- Stopping before failure modes, validation, or deployment implications.