Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Technical command
35% weight
Check fluency in three-statement modeling, DCF and comparables, driver-based forecasting, and Excel mechanics: INDEX/MATCH, Power Query, pivot models, plus any SQL, Tableau or Anaplan use.
Evidence to listen for
Commands the instruments, models, or reporting standards the role turns on
Can build the analysis rather than only interpret someone else's
Knows the assumptions inside a model and which ones actually drive the answer
Fluent in the frameworks and disclosure regimes that apply
Five-point scoring guide
1
Poor
Cannot explain the instruments or standards they claim to work with.
2
Needs Improvement
Interprets others' analysis but cannot build or defend it.
3
Satisfactory
Solid working command; thin on unfamiliar structures or standards.
4
Very Good
Builds the analysis and knows which assumptions actually move the answer.
5
Excellent
Builds linked three-statement and DCF models from scratch, names circularity and sensitivity handling, and shows real workbook structure and audit checks.
02
Evaluation factor
Deals and deliverables that closed
25% weight
Ask for specific deliverables: monthly close packs, board decks, annual budgets, capex business cases. Probe cycle times, dollar values, and how forecasts compared to actuals.
Evidence to listen for
Names transactions, filings, or reports they worked, with size, counterparties, and their own scope
Distinguishes their contribution from the deal team's
Knows what happened afterwards, including what underperformed
Can describe one that fell over and why
Five-point scoring guide
1
Poor
No completed work; describes process rather than outcomes.
2
Needs Improvement
Involved in transactions but cannot state their own scope.
3
Satisfactory
Real deliverables with adequate ownership; outcomes described loosely.
4
Very Good
Named transactions or filings with clear personal scope and honest post-mortems.
5
Excellent
Cites owned recurring deliverables with dates, budget size, and forecast accuracy, plus a decision leadership made from their analysis.
03
Evaluation factor
Risk judgement
25% weight
Probe how they treat assumptions: revenue driver sensitivity, downside cases, working capital swings, covenant headroom. Ask about a forecast miss they caught or missed.
Evidence to listen for
Distinguishes a modelled risk from a real one
States confidence and what would change their view
Comfortable disagreeing with a number that suits everybody
Knows the limits of the data behind a projection, especially over long horizons
Five-point scoring guide
1
Poor
Treats model output as truth; no sense of data limits.
2
Needs Improvement
Reports numbers without qualifying them; avoids unwelcome conclusions.
3
Satisfactory
Reasonable judgement; qualifies findings when prompted.
4
Very Good
States confidence unprompted and will hold an unpopular position on evidence.
5
Excellent
Stress tests assumptions unprompted, quantifies downside, and describes a variance they flagged early with the root cause traced.
04
Evaluation factor
Explaining it to decision-makers
15% weight
Assess how they present numbers to non-finance stakeholders: variance commentary, one-page summaries, defending an assumption to a CFO or business unit head.
Evidence to listen for
Explains a technical position to an investment committee, board, or regulator so they can act on it
Writes to the standard the audience is held to
Handles challenge without either caving or digging in
Works across legal, operations, and external counterparties
Five-point scoring guide
1
Poor
Cannot communicate beyond technical peers.
2
Needs Improvement
Explanations lose the audience or oversimplify to the point of error.
3
Satisfactory
Adequate with familiar audiences; less effective under challenge.
4
Very Good
Explains clearly to committees and regulators and holds up under challenge.
5
Excellent
Leads with the so-what, translates variance drivers into operational language, and holds their ground with evidence when challenged.
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