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 Onsite rounds at Uber.

What role is this question designed for?

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

Model Driver Acceptance Probability

Last updated: Apr 20, 2026

Quick Overview

This question evaluates a candidate's competency in production machine learning system design and operationalization, including label definition and unit of prediction, feature availability at decision time, label leakage avoidance, model selection, handling class imbalance, cold-start and delayed outcomes, evaluation and calibration, online experimentation and business metrics, and post-deployment concerns like fairness, feedback loops, and monitoring. It is commonly asked to assess the ability to apply conceptual understanding of labeling and statistical evaluation to practical deployment trade-offs; the domain is Machine Learning/Data Science and the level of abstraction spans practical application and system-level conceptual understanding.

Uber

Feb 27, 2026, 12:00 AM

Data Scientist

Onsite

Machine Learning

Design a machine learning system to predict the probability that a driver accepts a trip or delivery offer.

Your answer should cover:

the prediction target and label definition
the unit of prediction
candidate features available at decision time
how to avoid label leakage
model choices and why
handling class imbalance, cold start, and delayed outcomes
offline evaluation metrics and why calibration matters
online experimentation and business metrics
fairness, feedback loops, and model monitoring after deployment

Solution

Show

Submit Your Answer

Loading comments...

Browse More Questions

More Machine Learning•More Uber•More Data Scientist•Uber Data Scientist•Uber Machine Learning•Data Scientist Machine Learning