Diagnose Job-Application Decline: Funnel Stages and KPIs Analysis
Overview
This question evaluates a data scientist's skills in product analytics, diagnostic funnel analysis, KPI selection, time-series and causal reasoning, and supply–demand assessment across segmented cohorts within the Analytics & Experimentation domain.
LinkedIn
Aug 4, 2025, 10:55 AM
Data Scientist
Onsite
Analytics & Experimentation
77
0
Diagnostic Case: Drop in Job Applications
Context
You are a data scientist at a large job‑search platform. The primary metric "job applications submitted per day" has declined noticeably compared to recent baselines.
Task
Provide a structured plan to diagnose the decline:
- Full-funnel approach: How would you systematically break down the problem across the seeker-to-application funnel?
- KPIs to inspect: Which upstream and downstream metrics would you examine at each funnel stage?
- External vs. product causes: How would you separate seasonality/macro effects from product or operational issues?
- Demand–supply balance: What analyses would you run to assess equilibrium between job postings (supply) and job seekers (demand)?
- Segmentation: How would you segment (platform, user type, geography, job category, etc.) to localize the issue?
Hints: Consider time-series baselines, funnel drop-off, supply/demand ratios, cohort and geo splits, and external benchmarks.
Solution
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