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 hard difficulty Analytics & Experimentation 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.

Define market-only rider experience metrics

Quick Overview

This question evaluates a data scientist's competency in designing market-only rider experience metrics and a composite Market Balance Index, testing skills in marketplace metric specification, survival/hazard modeling, price-adjusted indexing, censoring and normalization rules, and experimental backtesting using server-side logs.

Market-only Rider Experience Metrics and Market Balance Index (MBI)

You are designing a metric suite for a rides marketplace where "rider experience" must reflect market balance (supply–demand dynamics) rather than app UI or vehicle quality. All metrics should be derivable from server-side marketplace logs and be robust to UI changes.

Tasks

Define a market-only metric suite that captures rider experience via supply–demand mechanics. Include, at minimum:
- Request Fill Rate within 5 minutes (FR5)
- Time-to-Match (TTM)
- Quoted pickup ETA at request time
- Realized pickup wait
- Rider wait-hazard (survival/hazard-based)
- Price-adjusted wait index
Provide precise metric definitions, including:
- Event and unit definitions (what constitutes an intent, request, match, pickup)
- Sampling windows and aggregation levels
- Censoring rules for unfulfilled requests and cancellations
- Holiday/outage exclusions and normalization
Propose a single composite Market Balance Index (MBI) with an explicit, computable formula and weights across sub-metrics. Explain scaling/normalization so MBI is comparable over markets and time.
Design a backtest that demonstrates sensitivity of the metric suite and MBI to supply/demand shocks (e.g., weather, events) but insensitivity to UI releases. Describe the study design and report illustrative results.

Quick Overview

Tasks

Define a market-only metric suite that captures rider experience via supply–demand mechanics. Include, at minimum:

Request Fill Rate within 5 minutes (FR5)
Time-to-Match (TTM)
Quoted pickup ETA at request time
Realized pickup wait
Rider wait-hazard (survival/hazard-based)
Price-adjusted wait index

Provide precise metric definitions, including:

Event and unit definitions (what constitutes an intent, request, match, pickup)
Sampling windows and aggregation levels
Censoring rules for unfulfilled requests and cancellations
Holiday/outage exclusions and normalization

Propose a single composite Market Balance Index (MBI) with an explicit, computable formula and weights across sub-metrics. Explain scaling/normalization so MBI is comparable over markets and time.

Design a backtest that demonstrates sensitivity of the metric suite and MBI to supply/demand shocks (e.g., weather, events) but insensitivity to UI releases. Describe the study design and report illustrative results.

Define market-only rider experience metrics

Quick Overview

Market-only Rider Experience Metrics and Market Balance Index (MBI)

Tasks

Solution

Submit Your Answer to Earn 20XP

Define market-only rider experience metrics

Quick Overview

Market-only Rider Experience Metrics and Market Balance Index (MBI)

Tasks

Solution

Submit Your Answer to Earn 20XP