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Define and integrate room ranking factors

Last updated: Mar 29, 2026

Quick Overview

This question evaluates knowledge of feature engineering, ranking and scoring systems, normalization and weighting of signals, cold-start handling, and experimental validation in the context of assigning rooms to meeting requests.

  • medium
  • Uber
  • Analytics & Experimentation
  • Software Engineer

Define and integrate room ranking factors

Company: Uber

Role: Software Engineer

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Onsite

Propose a ranking system for assigning rooms to meeting requests. Identify and justify priority factors such as room usage count, historical meeting duration fit, capacity match, equipment availability, and proximity. Describe how to combine these into a scoring function, how to handle cold-start and ties, and how you would run an experiment (e.g., A/B test) to validate and tune the weights.

Quick Answer: This question evaluates knowledge of feature engineering, ranking and scoring systems, normalization and weighting of signals, cold-start handling, and experimental validation in the context of assigning rooms to meeting requests.

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Uber logo
Uber
Aug 1, 2025, 12:00 AM
Software Engineer
Onsite
Analytics & Experimentation
1
0

Design a Room-Ranking System for Meeting Requests

Context

You are building a service that assigns conference rooms to meeting requests across multiple buildings. Each meeting request includes time, expected attendees, duration, equipment needs, and location preferences. Rooms have capacities, equipment, locations, and booked/free time blocks. The goal is to rank eligible rooms and pick the best one.

Task

Propose a ranking system that:

  1. Identifies and justifies priority factors, including (but not limited to):
    • Room usage count (load balancing)
    • Historical meeting duration fit
    • Capacity match
    • Equipment availability
    • Proximity
  2. Combines these factors into a scoring function with clear normalization and weighting.
  3. Handles cold-start scenarios (new rooms or new meeting types) and tie-breaking.
  4. Describes how to validate and tune the weights via an experiment (e.g., A/B test), including metrics and guardrails.

Solution

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