##### Scenario Instacart launched Ultrafast Delivery in Miami two months ago and wants to measure its impact on user order volume. ##### Question Design an approach to estimate the feature’s causal impact on orders. How would you choose an appropriate control geography? Describe the mechanics of your chosen method (e.g., DiD, synthetic control, propensity-score matching). If using a linear mixed-effects model, which variables are fixed versus random? ##### Hints Cover identification, parallel-trend checks, robustness tests, and metric calculation.

This question evaluates a data scientist’s competency in causal inference and experimental analytics, focusing on panel-data methods and control-group selection for measuring the impact of a city-level product launch.

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 medium difficulty Analytics & Experimentation question, commonly asked during Technical Screen rounds at Instacart.

What role is this question designed for?

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

Measure Ultrafast Delivery's Impact Using Synthetic Control Method

Scenario

Instacart launched Ultrafast Delivery in Miami two months ago and wants to measure its causal impact on user order volume.

Assume you have panel data at the daily or weekly level for multiple geographies (cities/ZIPs), including Miami and a set of non-launched geographies, with pre- and post-launch history. You also have covariates like baseline demand, seasonality, retailer mix, promos, and weather.

Task

Design an approach to estimate the feature’s causal impact on orders and describe how you would select an appropriate control geography.

Requirements

Control Geography Selection
- How would you choose and validate a control geography (or set of geographies)?
Method Mechanics
- Describe the mechanics of your chosen causal method (e.g., Difference-in-Differences, Synthetic Control, Propensity-Score Matching). Be explicit about identification assumptions and how you’ll check parallel trends.
Linear Mixed-Effects Variant
- If you choose a linear mixed-effects model, specify which variables would be fixed versus random.
Robustness and Validation
- Discuss parallel-trend checks, placebo tests, sensitivity analyses, and how to calculate the impact metric and uncertainty.

Scenario

Instacart launched Ultrafast Delivery in Miami two months ago and wants to measure its causal impact on user order volume.

Requirements

Control Geography Selection

How would you choose and validate a control geography (or set of geographies)?

Method Mechanics

Describe the mechanics of your chosen causal method (e.g., Difference-in-Differences, Synthetic Control, Propensity-Score Matching). Be explicit about identification assumptions and how you’ll check parallel trends.

Linear Mixed-Effects Variant

If you choose a linear mixed-effects model, specify which variables would be fixed versus random.

Robustness and Validation

Discuss parallel-trend checks, placebo tests, sensitivity analyses, and how to calculate the impact metric and uncertainty.

Measure Ultrafast Delivery's Impact Using Synthetic Control Method

Quick Overview

Scenario

Task

Requirements

Solution

Comments (0)

Measure Ultrafast Delivery's Impact Using Synthetic Control Method

Quick Overview

Scenario

Task

Requirements

Solution

Comments (0)