Prioritize a new warehouse proposal with data

Quick Overview

This question evaluates demand forecasting, network optimization, five-year NPV financial modeling, experiment and quasi-experiment design for incrementality estimation, sensitivity analysis, and stakeholder communication within the analytics & experimentation domain for data science roles focused on warehouse/fulfillment center decisions.

Prioritize a new warehouse proposal with data

Company: Amazon

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: hard

Interview Round: Technical Screen

Stakeholders ask whether to build a new fulfillment center (FC). You have partial data: daily demand by metro, current FC capacities and per-FC variable costs, average delivery time vs. distance, and lease/CapEx options. 1) Outline the end-to-end analysis plan to recommend build vs. lease vs. defer: demand forecasting method, service-level targets, network optimization objective (e.g., minimize total cost subject to 95% next-day coverage), and key constraints. 2) Show a back-of-the-envelope model with explicit assumptions to estimate NPV over 5 years, including cannibalization and ramp curves. 3) Describe the experiment or quasi-experiment you would run before committing (geo holdouts, incrementality via synthetic control, or simulation with historical replays), with success metrics and stopping rules. 4) Provide a sensitivity analysis: which three parameters most threaten the decision and how you would bound them with additional data. 5) Draft a one-slide stakeholder narrative with the recommendation and the top two risks plus mitigations.

Quick Answer: This question evaluates demand forecasting, network optimization, five-year NPV financial modeling, experiment and quasi-experiment design for incrementality estimation, sensitivity analysis, and stakeholder communication within the analytics & experimentation domain for data science roles focused on warehouse/fulfillment center decisions.

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Oct 13, 2025, 9:49 PM
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Build vs. Lease vs. Defer: New Fulfillment Center Decision

Context

You are evaluating whether to open a new fulfillment center (FC) to improve delivery speed and reduce costs. You have:

  • Daily demand by metro/zip.
  • Current FC capacities and variable costs.
  • Average delivery time as a function of distance.
  • Lease and build (CapEx) options with cost details.

Assume the goal is to maximize long-run free cash flow while meeting customer service-level targets (e.g., 95% next-day coverage in target metros) under operational constraints.

Tasks

  1. Outline an end-to-end analysis plan: demand forecasting approach, service-level targets, network optimization objective and constraints.
  2. Create a back-of-the-envelope (BOTE) 5-year NPV model with explicit assumptions, including cannibalization of existing FCs and ramp-to-steady-state utilization.
  3. Propose an experiment or quasi-experiment (e.g., geo holdouts, synthetic control, or historical replay simulation) to estimate incrementality prior to committing. Include success metrics and stopping rules.
  4. Provide a sensitivity analysis: identify the three most critical parameters, explain why they matter, and how to bound them with additional data.
  5. Draft a one-slide stakeholder narrative: recommendation, top two risks, and mitigations.
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