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 depth
35% weight
Check hands-on command of content protection stacks: Widevine or PlayReady DRM tiers, forensic watermark extraction, HDCP rules, plus tooling for CDN log review and leak source tracing.
Evidence to listen for
Command of the specific attack surface, tooling, and controls the role covers
Understands how the underlying system works, not just how the tool reports on it
Can explain an attack or control chain end to end
Distinguishes what they found themselves from what a scanner flagged
Five-point scoring guide
1
Poor
Tool operator only; no understanding of the systems underneath.
2
Needs Improvement
Runs tooling but cannot explain findings or how the attack works.
3
Satisfactory
Solid working knowledge; depth thins outside familiar tooling.
4
Very Good
Strong command of the domain; explains attack and control chains clearly.
5
Excellent
Names specific DRM configurations and watermark vendors, explains how a leaked stream was traced back to an individual account or screener.
02
Evaluation factor
Real incidents and findings
30% weight
Probe actual enforcement casework: volume of DMCA and platform takedowns issued monthly, notice-and-staydown work, infringing seller networks dismantled, and pre-release leak investigations they ran end to end.
Evidence to listen for
Brings specific incidents, findings, or audits they personally worked
States their own role rather than the team's
Describes what was actually at risk and what changed afterwards
Can talk about a finding that turned out to be wrong
Five-point scoring guide
1
Poor
No hands-on work; knowledge is entirely certification or coursework.
2
Needs Improvement
Limited exposure; cannot describe their contribution to an incident.
3
Satisfactory
Real casework with adequate detail; ownership sometimes vague.
4
Very Good
Specific incidents with clear personal scope and what changed after.
5
Excellent
Cites concrete numbers (notices sent, URLs removed, repeat-infringer sites delisted) and walks through one leak case from detection to resolution.
03
Evaluation factor
Risk judgement
20% weight
Assess how they triage: which infringements get lawyers, which get a takedown bot, and how they weigh revenue leakage against enforcement cost and false-positive risk to legitimate fans.
Evidence to listen for
Prioritises by actual exploitability and business impact, not raw severity scores
Can argue for accepting a risk as well as fixing it
Knows the difference between a finding and a problem
Does not cry wolf or wave things through
Five-point scoring guide
1
Poor
Treats every finding as critical, or waves real risk through.
2
Needs Improvement
Follows severity scores mechanically; no business context.
3
Satisfactory
Reasonable prioritisation; less confident arguing for risk acceptance.
4
Very Good
Prioritises by exploitability and impact; can justify accepting a risk.
5
Excellent
Prioritises by measurable harm rather than volume, and can describe an infringement they deliberately left alone with sound reasoning.
04
Evaluation factor
Getting things fixed
15% weight
Look for evidence they moved platforms, studios, or internal engineering to act: escalation paths with YouTube, Amazon, or Cloudflare trust and safety, and security fixes they got prioritised.
Evidence to listen for
Writes findings engineers can act on rather than a wall of output
Has persuaded a team to fix something they did not want to fix
Explains risk to executives in business terms
Works with the org rather than policing it
Five-point scoring guide
1
Poor
Adversarial with engineering; findings never get fixed.
2
Needs Improvement
Reports are unactionable; no influence beyond raising tickets.
3
Satisfactory
Adequate reporting; relies on mandate rather than persuasion.
4
Very Good
Actionable findings and a real record of getting fixes shipped.
5
Excellent
Holds named platform escalation contacts, shows closed loops where a repeat leak vector was engineered out, not just repeatedly reported.
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