Interview scorecard template

Autonomous Vehicle Safety Analyst interview scorecard

Evaluate Autonomous Vehicle Safety Analyst candidates across 4 weighted areas: method and rigour, real casework, interpretation and judgement, and reporting and testimony. Method and rigour leads at 35%, so check command of hazard analysis methods: HARA, STPA, FMEA, fault tree analysis, and how they applied ISO 26262 ASIL decomposition or ISO 21448. Use the rubric to compare role-specific evidence consistently.

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TL;DR
For method and rigour, look for evidence the candidate names the specific method used per hazard, explains ASIL or SOTIF rationale, and cites acceptance criteria they helped define. For real casework, look for evidence the candidate describes real incidents triaged, fleet miles or scenario counts reviewed, and named artefacts such as UL 4600 safety case chapters. Apply the written 1–5 anchors to every answer, record the evidence behind each rating, and use the factor weights to reach a consistent overall assessment.
Complete evaluation framework

What to assess and how to score it

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

Method and rigour

35% weight

Check command of hazard analysis methods: HARA, STPA, FMEA, fault tree analysis, and how they applied ISO 26262 ASIL decomposition or ISO 21448 SOTIF triggering condition analysis.

Evidence to listen for

  • Follows and can justify an established methodology
  • Understands contamination, bias, and chain of custody as they apply to the field
  • Knows the limits of their techniques and says so
  • Documents procedure so results are reproducible and defensible

Five-point scoring guide

1
Poor

Careless method; unaware of contamination, bias, or procedural integrity.

2
Needs Improvement

Knows procedures but applies them inconsistently; gaps in documentation.

3
Satisfactory

Sound standard practice; less certain outside familiar techniques.

4
Very Good

Rigorous and well documented; understands the limits of each method.

5
Excellent

Names the specific method used per hazard, explains ASIL or SOTIF rationale, and cites acceptance criteria they helped define.

02
Evaluation factor

Real casework

25% weight

Probe actual work on a driving automation programme: disengagement and collision triage, ODD definition, scenario libraries in CARLA or resimulation, safety case evidence they authored.

Evidence to listen for

  • Brings specific cases, sites, or projects rather than general description
  • States their own role and what they personally handled
  • Can describe an ambiguous or degraded case and how they proceeded
  • Knows what happened to the work afterwards

Five-point scoring guide

1
Poor

No hands-on casework; experience is entirely academic.

2
Needs Improvement

Limited exposure; cannot describe their own contribution clearly.

3
Satisfactory

Real casework with adequate detail; ownership sometimes vague.

4
Very Good

Specific cases with clear personal scope and outcomes.

5
Excellent

Describes real incidents triaged, fleet miles or scenario counts reviewed, and named artefacts such as UL 4600 safety case chapters.

03
Evaluation factor

Interpretation and judgement

25% weight

Test how they reason from sparse event data: distinguishing perception misdetection from planner error, judging residual risk, deciding whether a release gate should hold.

Evidence to listen for

  • Separates what the evidence shows from what they infer
  • States confidence levels and what would change their conclusion
  • Comfortable saying the result is inconclusive
  • Handles pressure to reach a preferred conclusion without bending

Five-point scoring guide

1
Poor

Overstates findings; no separation of evidence from inference.

2
Needs Improvement

Reaches conclusions the evidence does not support; uneasy with uncertainty.

3
Satisfactory

Reasonable judgement; qualifies findings when prompted.

4
Very Good

Clearly separates evidence from inference and states confidence unprompted.

5
Excellent

Walks through a specific ambiguous event, states the competing hypotheses, and explains the evidence that settled the release decision.

04
Evaluation factor

Reporting and testimony

15% weight

Assess written and verbal reporting to engineering leads, regulators, and NHTSA or state DMV submissions; ask for examples of safety review board presentations or corrective action records.

Evidence to listen for

  • Writes findings that a non-specialist can act on
  • Has presented or defended work to an external audience: court, client, review board, publication
  • Withstands challenge without overclaiming or retreating
  • Keeps records that hold up to scrutiny

Five-point scoring guide

1
Poor

Cannot communicate findings; records would not withstand review.

2
Needs Improvement

Reporting is unclear or incomplete; avoids external scrutiny.

3
Satisfactory

Adequate reports; limited experience defending work externally.

4
Very Good

Clear reporting and real experience presenting to an external audience.

5
Excellent

Produces clear, traceable findings; has defended conclusions to a safety board or regulator without softening the risk.

Evidence-led prompts

Interview questions for a Autonomous Vehicle Safety Analyst

Use these prompts to surface evidence for the weighted factors above and compare candidates against the same role-specific criteria.

  1. 01

    Can you describe your experience developing or testing autonomous vehicle systems?

  2. 02

    Can you give an example of how you handled a critical safety issue?

  3. 03

    Have you worked on creating or validating safety-critical software?

  4. 04

    What methodologies do you use for failure mode and effects analysis?

  5. 05

    How do you approach risk assessment in autonomous vehicle projects?

See the complete Autonomous Vehicle Safety Analyst question set
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