Business Context and Metrics Understanding Questions
Understand the broader business context for technical or operational work and identify relevant performance metrics. This includes recognizing the key performance indicators for different functions, translating technical outcomes into business impact, scoping a problem with success metrics and constraints, and using metrics to prioritize trade offs. Candidates should demonstrate how they would frame a problem in business terms before proposing technical or operational solutions.
HardSystem Design
0 practiced
Design a measurement strategy to compute unique users and cross-device engagement metrics under GDPR constraints while minimizing PII storage. Describe approaches such as salted hashed identifiers, differential privacy, or aggregated bucketing, list trade-offs between accuracy and privacy, and explain how you would validate measurement accuracy.
HardTechnical
0 practiced
You're building global revenue dashboards across regions with different local currencies and VAT. Describe how you would standardize and present consolidated metrics: exchange-rate strategy (real-time vs end-of-day vs monthly average), handling VAT/GST (gross vs net), normalization for local price differences, and how you'd document assumptions for finance and product teams.
MediumTechnical
0 practiced
Using transactions(transaction_id, user_id, amount, occurred_at), write SQL (standard SQL / BigQuery) to compute monthly cohort LTV: for each cohort month compute cumulative revenue per user for days 0–90 (first 90 days). Show key assumptions and how you would handle refunds or negative transactions.
MediumTechnical
0 practiced
Describe a practical process to set realistic KPI targets and forecasts for the next quarter. Include methods for trend analysis, seasonality adjustment, top-down versus bottom-up forecasting, incorporating stakeholder inputs, and communicating forecast uncertainty (scenario ranges and confidence intervals).
HardTechnical
0 practiced
Design an approach to measure the incremental impact of a large marketing campaign when seasonality and overlapping promotions exist. Describe experimental design (randomized holdouts or geographic holdouts), analysis methods such as difference-in-differences or uplift modeling, operational constraints, and how you would allocate budget for testing.
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