How do I approach Analytics & Experimentation interview questions?

Analytics & Experimentation questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master analytics & experimentation interviews.

What difficulty level is this interview question?

This is a hard difficulty Analytics & Experimentation question, commonly asked during Technical Screen rounds at Uber.

What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Uber during technical interviews.

Choose between A/B and switchback for spillovers

Quick Overview

This question evaluates experimental-design and causal-inference competencies, specifically handling interference and spillovers, defining experimental units and treatment assignment, drawing causal DAGs, identifying bias sources, selecting primary and guardrail metrics, and pre-specifying decision rules.

Airport Driver-Queue Algorithm: Experiment Design and Causal Reasoning

Background

A new driver-queue algorithm is being tested at a single airport with multiple terminals. The algorithm can reassign drivers across terminals, which may influence nearby terminals and the overall airport driver pool.

Task

Decide whether to use a classic user-level A/B test or a switchback/geo-time experiment. Then:

Define the experimental unit and explain how treatment will be assigned.
Draw and explain a causal DAG to reason about interference and spillovers across terminals and over time.
Justify your experimental design choice given potential interference.
Identify main bias sources (e.g., time trends, weather, event traffic) and propose mitigation strategies (e.g., blocking by hour/day, CUPED, randomization inference).
Specify:
- Primary success metric
- Guardrail metrics
- A clear, pre-specified go/no-go decision rule

Assume you can toggle the algorithm on/off at the airport level and collect standard operational metrics (wait times, cancellations, earnings, throughput).

Quick Overview

Task

Decide whether to use a classic user-level A/B test or a switchback/geo-time experiment. Then:

Define the experimental unit and explain how treatment will be assigned.

Draw and explain a causal DAG to reason about interference and spillovers across terminals and over time.

Justify your experimental design choice given potential interference.

Identify main bias sources (e.g., time trends, weather, event traffic) and propose mitigation strategies (e.g., blocking by hour/day, CUPED, randomization inference).

Specify:

Primary success metric
Guardrail metrics
A clear, pre-specified go/no-go decision rule

Assume you can toggle the algorithm on/off at the airport level and collect standard operational metrics (wait times, cancellations, earnings, throughput).

Choose between A/B and switchback for spillovers

Quick Overview

Airport Driver-Queue Algorithm: Experiment Design and Causal Reasoning

Background

Task

Solution

Comments (0)

Choose between A/B and switchback for spillovers

Quick Overview

Airport Driver-Queue Algorithm: Experiment Design and Causal Reasoning

Background

Task

Solution

Comments (0)