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 Upstart.

What role is this question designed for?

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

Design Experiment to Measure Airport Surge-Pricing Impact

Quick Overview

This question evaluates expertise in experimental design and causal inference for two-sided marketplaces, including competencies in randomization/unit selection, handling interference and spillovers, clustering, timing windows, and choice of primary and secondary metrics.

Experiment Design: Causal Impact of Airport Surge-Pricing Push Notifications on Driver Supply

Context

You operate a two-sided ride-hailing marketplace. A new push notification is sent to eligible drivers when the airport is in surge, aiming to attract more drivers to the airport. Drivers within and around the airport can see and respond to the push at overlapping times, so interference (spillovers) between treated and untreated drivers is plausible.

Task

Design an experiment to measure whether the push notification causally increases driver supply at the airport while handling potential interference.

Please address:

Experimental design: randomization unit(s), holdouts, timing windows, and any clustering.
Primary and secondary success metrics to track.
How you will detect and account for spillovers on untreated drivers.
How you will identify causal impact in the presence of interference (e.g., geographic clustering, holdout zones, difference-in-differences, network interference adjustments).

Quick Overview

Context

Task

Design an experiment to measure whether the push notification causally increases driver supply at the airport while handling potential interference.

Please address:

Experimental design: randomization unit(s), holdouts, timing windows, and any clustering.

Primary and secondary success metrics to track.

How you will detect and account for spillovers on untreated drivers.

How you will identify causal impact in the presence of interference (e.g., geographic clustering, holdout zones, difference-in-differences, network interference adjustments).

Design Experiment to Measure Airport Surge-Pricing Impact

Quick Overview

Experiment Design: Causal Impact of Airport Surge-Pricing Push Notifications on Driver Supply

Context

Task

Solution

Comments (0)

Design Experiment to Measure Airport Surge-Pricing Impact

Quick Overview

Experiment Design: Causal Impact of Airport Surge-Pricing Push Notifications on Driver Supply

Context

Task

Solution

Comments (0)