Deep technical project narrative and lessons learned Questions
Prepare detailed discussion of a significant project: the problem, your approach, technical decisions and trade-offs, challenges and how you overcame them, outcome, and what you learned. Practice explaining this clearly in 10-15 minutes, leaving time for questions.
MediumTechnical
0 practiced
Explain your approach to model explainability during the project: which techniques (SHAP, LIME, attention maps) you used, how you validated explanations, how you surfaced them to stakeholders, and a concrete example where explainability changed a product decision.
MediumTechnical
0 practiced
Describe your design and execution of randomized experiments (A/B tests) to validate the model in production. Include sample size or power calculations, primary and secondary metrics, experiment duration, ramping strategy, and how you handled multiple comparisons and early stopping concerns.
MediumTechnical
0 practiced
Explain how you selected evaluation metrics for the project. Discuss trade-offs among precision, recall, F1, AUC, calibration, business KPIs, and differences between offline and online metrics. Explain how you prioritized which metrics drove model selection and acceptance gates.
HardTechnical
0 practiced
Deliver a 10-15 minute deep-dive narrative that centers on the most consequential technical decision you made in the project. Include alternatives with pros/cons, the quantitative experiments and metrics you used (include sample numbers), cost/performance trade-offs, how you validated the decision in production, and what you would change in hindsight.
MediumTechnical
0 practiced
Tell me about a time you onboarded or mentored a junior engineer as part of this project. Describe the plan you used to transfer knowledge, the mix of shadowing vs hands-on tasks, code review strategy, documentation created, and how you measured the mentee's readiness for independent work.
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