How do I approach Machine Learning interview questions?

Machine Learning questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master machine learning interviews.

What difficulty level is this interview question?

This is a medium difficulty Machine Learning 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 Push-Notification System for Airport Surge Pricing

Quick Overview

This question evaluates a data scientist's competency in designing ML-driven real-time decision systems, covering feature engineering, predictive modeling for supply–demand imbalance, budgeted ranking for notifications, and operational constraints like per-driver throttling; it is categorized under Machine Learning for a Data Scientist role.

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.

Quick Overview

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.

Design Push-Notification System for Airport Surge Pricing

Quick Overview

Designing Airport Surge Push Notifications for Drivers

Context

Task

Hints

Solution

Comments (0)

Design Push-Notification System for Airport Surge Pricing

Quick Overview

Designing Airport Surge Push Notifications for Drivers

Context

Task

Hints

Solution

Comments (0)