Challenge and validate assumptions
Capital OneData Scientist · Technical Screen
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This question evaluates a data scientist's competency in identifying fragile business assumptions, conducting sensitivity analysis, and designing experiments and observational studies to validate parameters related to demand, price elasticity, cannibalization, supply constraints, labor learning curves, regional heterogeneity, and promotional decay.
Which assumptions in the vegan-burger business case are most likely to be wrong or unstable, and how would you validate them? Discuss demand forecast uncertainty, price elasticity, cannibalization of the classic burger, substitution/halo, supplier reliability and minimums, learning-curve effects on labor time, kitchen capacity constraints, regional heterogeneity, and promo lift decay. Propose a sensitivity analysis plan (key variables, plausible ranges, and tornado chart) and an experiment/observational design to de-bias estimates.
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