Research Operations Partner in Chelmsford

About Deep Signal

Deep Signal is a transcript-based psychological risk screening engine for high-trust roles. Rather than relying on self-report questionnaires, Deep Signal analyses interview transcripts the way an experienced clinical psychologist would: reading how someone talks about themselves and others to surface patterns that are very difficult to fake. The result is a classification and diagnostic assessment that gives organisations clinical-depth insight into a candidate's psychological risk profile at a fraction of the cost and speed of traditional clinical assessment. The technology sits at the intersection of clinical psychology, applied AI, and high-stakes vetting.

The team

Deep Signal is a small team by design at this stage, operating as an intrinsic part of The Hacking Games. Mark Loftus — clinical psychologist and the architect of Deep Signal, currently the primary source of clinical judgement on the project. A retained technical/AI advisor is running the software development of the scoring pipeline and infrastructure. A search is underway for a senior clinical/forensic psychologist to build clinical depth alongside Mark.

This role would be the first dedicated hire focused specifically on the discipline and rigour behind the scoring methodology and pipeline itself.

How this role fits in

This role exists to take on rigorous testing, clean record-keeping, and clear diagnostic evidence — freeing Mark to spend his time on the clinical and strategic judgement calls that genuinely need his expertise, while you make sure that judgement is being tested properly rather than taken on faith. You'll report directly to Mark and work closely with our technical advisor on the underlying pipeline infrastructure.

What You Will Do

• Testing and calibration discipline: Design and run structured tests every time we change a scoring prompt, marker, or protocol — using a fixed reference set of transcripts.
• Diagnostics and analysis: Analyse which markers and signals are actually driving the model's classifications, and flag where something expected isn't showing up as expected.
• Documentation: Build the habit of documenting reasoning and decisions as they're made.
• A standing responsibility to flag: Regularly look at results that raise questions and surface these clearly and rigorously.

What we're looking for

This is not a conventional data science role, and it's not a clinical psychology role either — it sits in between, and we're open-minded about which side of that line you come from, provided both are genuinely present.

What You'll Bring

• A strong quantitative/analytical background — comfortable with statistical concepts.
• Real intellectual curiosity about psychology.
• A natural inclination toward rigour and process for its own sake.
• Comfort working in an early-stage, still-forming environment.

You might come from:

• A research assistant or lab manager role attached to a computational or quantitative psychology research group.
• A postgraduate or recent research background in computational psychiatry, psychometrics, or applied natural language processing.
• Another applied research or data role where you were responsible for the rigour behind someone else's substantive decisions.

What success looks like in the first few months

• You've built and are running a structured testing process for pipeline changes.
• There's a running, organised record of what's changed in the scoring pipeline and why.
• You've independently spotted and flagged and suggested a resolution for at least one thing that is genuinely material to the success of the Deep Signal engine.

Future prospects

This is a genuinely early-stage role on a product we believe has significant potential, in a small and growing team. As the calibration and validation work matures over the coming year, this role has real scope to grow.

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