Quantitative Analysis and Metrics Interpretation Questions

Core skills for working with numeric business data: calculating and interpreting key metrics, comparing options numerically, identifying trends and anomalies, performing variance checks, and testing assumptions. Includes reading dashboards and query results, extracting meaningful insights from revenue and operational metrics, segmenting data, identifying outliers, and understanding what metrics indicate about business performance. Candidates should be comfortable stating and justifying assumptions, performing simple break even and cost benefit reasoning, and translating numbers into prioritized actions or follow up analyses. This topic covers cross functional metric types from sales and operations to product and marketing, and emphasizes structured thinking, correct metric definitions, basic descriptive statistics, and how to use data to support recommendations.

MediumTechnical

39 practiced

Given an events table in PostgreSQL with schema events(user_id uuid, event_date timestamp), write a SQL query (Postgres) that returns weekly active users (WAU) for each of the last 8 Mondays (week starting date) and the week-over-week percentage change compared to the prior week. Weeks should start on Monday. Include null-safe handling for the first week in the result.

HardTechnical

48 practiced

You observe that channel A shows a higher conversion rate than channel B, but channel A users tend to be smaller in number and more engaged. Design a statistical approach to compare true channel performance fairly: specify data needs, adjustments (e.g., propensity score weighting, stratification, regression controls), limitations of each approach, and how to present adjusted results to marketing for decision-making.

MediumTechnical

50 practiced

You discover duplicate order records in the order table that are inflating revenue totals. Outline a step-by-step remediation plan: detection queries, estimating the revenue impact, data pipeline fixes, short-term rollback or restatement considerations, verification tests, monitoring to prevent recurrence, and recommended owners for each step.

EasyTechnical

38 practiced

How would you segment Monthly Recurring Revenue (MRR) to identify which customer groups are driving growth? Provide six segmentation dimensions you would use, explain the rationale for each, and name one specific metric to track per segment that helps indicate healthy expansion or early warning signs.

MediumTechnical

62 practiced

Design five SLA metrics for a 3PL logistics vendor that handles inbound returns and last-mile delivery. For each metric specify the definition, measurement window, minimum target, and an example penalty or incentive structure tied to the SLA.

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