Design Push-Notification System for Airport Surge Pricing
Quick Overview
Design Push-Notification System for Airport Surge Pricing evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Design Push-Notification System for Airport Surge Pricing
Company: Upstart
Role: Data Scientist
Category: Machine Learning
Difficulty: medium
Interview Round: Technical Screen
##### Scenario
Airport surge pricing push notifications: deciding which drivers to notify when supply < demand
##### Question
How would you design a push-notification ranking system that determines how many drivers to target and which drivers to include when airport surge pricing occurs? Why could a simple distance-radius rule perform poorly, and what improvements would you propose? Besides ETA, which additional features or metrics would you engineer to decide whether to send a notification? If neighborhood supply-demand imbalance may be predictive, how would you detect whether a region is imbalanced enough to trigger a notification?
##### Hints
Discuss feature engineering, predictive modeling, supply-demand signals, real-time data, model evaluation.
Quick Answer: Design Push-Notification System for Airport Surge Pricing evaluates core ML concepts, assumptions, math intuition, training/evaluation trade-offs, and practical failure modes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Design Push-Notification System for Airport Surge Pricing
Designing Airport Surge Push Notifications for Drivers
Context
You are building a real-time system for a ride-hailing platform. When an airport experiences a surge (passenger demand exceeds available drivers), the system should decide:
How many drivers to notify (the "budget").
Which specific drivers to notify (the "ranking").
Assume you have real-time telemetry for drivers, trips, and demand forecasts, and you can send push notifications with per-driver throttling.
Task
Outline a system to determine how many drivers to target and which drivers to include when airport surge pricing occurs.
Explain why a simple distance-radius rule (e.g., notify anyone within 10 miles) can perform poorly, and propose improvements.
Besides ETA, list additional features/metrics you would engineer to decide whether to send a notification.
If neighborhood-level supply–demand imbalance is predictive, describe how you would detect whether a region is imbalanced enough to trigger a notification.
Hints
Discuss feature engineering, predictive modeling, supply–demand signals, real-time data, and model evaluation.
Clarifying Questions to Ask Guidance
Clarify the task, data shape, labels, constraints, and evaluation metric.
State assumptions behind the math or modeling technique you choose.
Connect theory to practical training, debugging, and deployment implications.
What a Strong Answer Covers Guidance
Correct definitions and formulas where the prompt requires them.
A practical explanation of how the method behaves on real data.
Trade-offs, failure modes, diagnostics, and mitigation strategies.
Evaluation choices that match the product or modeling objective.
Follow-up Questions Guidance
How would noisy labels, class imbalance, or distribution shift affect the answer?