Hiring nowInformation integrity, authenticity and democratic resilience

Synthetic Media Forensics Analyst

Also called Deepfake Analyst

A Synthetic Media Forensics Analyst investigates suspected fake or generated images, audio and video and reports what can be shown. Companies rely on them to act on manipulation claims without wrongly blaming anyone.

What they do

They take a piece of suspect media and work out where it came from and what has been done to it. They check provenance data, run forensic and verification tools, and compare the file against earlier copies and other sources. They look for corroboration outside the file: who posted it first, what the scene shows, whether the audio fits the setting. They test their own conclusions against alternatives. They write up what they found, how sure they are and what would change their mind. They also feed patterns back to product, policy and red teaming colleagues so the company can see how its systems get misused.

What a strong hire delivers

Within the first months, a strong hire gives the company a repeatable way to handle manipulation cases, from intake to a finished report. Senior people can rely on their findings and act on them. They build a clear confidence scale that non-specialists understand. They reduce wrongful attributions, show which cases need escalation, and leave a case log others can learn from.

How you can tell they are good

Ask them to walk through a past case and show a report with the uncertainty left in. Good candidates explain what tools could not tell them and which alternative explanations they ruled out. They separate 'manipulated' from 'generated' from 'misleading context'. Be wary of anyone who treats a detector score as proof or speaks with certainty from one signal.

Why it is hard to fill

Hardly anyone has this exact title. The work sits between digital forensics, journalism verification and trust and safety, and each background covers only part of it. Forensics people may write reports nobody outside their field can read. Journalists may lack technical depth. Generation methods change quickly, so candidates must show they keep learning. Evidential discipline is the rarest piece and the one you should test hardest.

Where to find them

Look in digital forensics teams, newsroom verification and open source investigation desks, and trust and safety investigations groups at platforms. Fact-checking organisations, election integrity programmes and research groups studying online manipulation are also good sources. Some come from security teams doing threat intelligence, and some from academic media forensics labs. Titles include deepfake analyst, investigator, verification specialist, disinformation analyst and threat intelligence analyst.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for a Synthetic Media Forensics Analyst

  1. Describe a case where you investigated suspected manipulated media. What did you conclude, and how confident were you?

    Strong answers give a concrete case, the evidence used, a stated confidence level and what stayed unknown. Look for corroboration beyond the file itself. Worry if they only describe a tool output or claim certainty without showing the reasoning.

  2. A detection tool says a video is 95 percent likely to be synthetic. What do you do next?

    They treat the score as one signal, check how the tool behaves on compressed or edited files, and look for provenance and corroboration. They consider false positives. Worry if they accept the score or reject it without testing.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are looking for a Synthetic Media Forensics Analyst to investigate suspected manipulated or generated media and tell us clearly what can and cannot be shown. You will work with product, policy, security and research teams, and your reports will inform decisions that matter to our users and to us.

What you will do

  • Investigate suspected manipulated or AI-generated images, audio and video
  • Validate provenance and authenticity using forensic and verification tools
  • Gather corroborating evidence from outside the file
  • Write forensic reports that state findings, uncertainty and alternative explanations
  • Advise on attribution and avoid unsupported claims
  • Work with red teaming and policy colleagues to spot misuse patterns
  • Maintain a case log and improve our investigation methods

What you will bring

  • Demonstrated investigations of manipulated media, with reports you can discuss
  • Sound evidential reasoning and clear handling of uncertainty
  • Hands-on use of media forensics and verification tools
  • Working knowledge of content provenance approaches
  • Ability to explain technical findings to non-specialists
  • Background in digital forensics, journalism, trust and safety or social research

Nice to have

  • Experience testing generation tools to understand their artefacts
  • Experience supporting election or crisis response work
  • Experience with AI red teaming

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Information integrityAdvancedAssess manipulated content and evidential authenticity
  • Content provenanceAdvancedMaintain traceable origin and transformations of media
  • AI red teamingWorkingTest systems adversarially under authorisation
  • Technical communicationWorkingExplain evidence and limitations to relevant readers

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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