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Illustrative scores · independent of your workspace edits

Data & analytics · Example candidate

Explain a change in reported revenue

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Task outcome

Corrected the revenue count; all 3 reconciliation checks passed.

Delivered Query + decision memo

Evaluation score4.0/5Illustrative score

Score breakdown

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Data investigation4.0/5

Finds repeated order records before interpreting the revenue trend.

Metric correctness4.0/5

Reconciles the latest paid records. Refund and currency rules remain open.

Analytical judgment5.0/5

Separates a reporting error from a decline whose cause is not established.

Decision readiness3.0/5

States the limitation clearly, but does not specify the next causal investigation.

How to read these scores

1 = major gaps · 3 = partially meets · 5 = fully meets. This example weights all four criteria equally.

These scores and excerpts are illustrative, not a live evaluation or a hiring recommendation. In the product, evaluations score submitted work against the configured criteria; missing evidence is identified separately.

Full findings and sources
01

Checks data quality before interpretation

Supported in this example

02

Reconciles the metric definition

Supported in this example

03

Distinguishes observation from cause

Follow-up needed

Optional follow-up

What would you check before attributing the remaining change to customer behavior?

Illustrative scores and evidenceInspect an actual saved grading example ↗
Source [01] · Illustrative excerpt

Data audit

Locate duplicate order records.

quality_checks.sql

SELECT order_id, COUNT(*)
FROM orders
GROUP BY order_id
HAVING COUNT(*) > 1;
What the source supports
The query identifies orders represented by multiple rows before aggregation.
What remains open
Repeated rows may be legitimate updates; the order lifecycle must also be understood.