This is a description of method, not a client account. It shows how the submission gate behaves when the requirement is platform depth in a regulated environment and the market is full of aspirational profiles.
The problem shape
Data and AI requirements attract keyword-rich profiles. The platforms are widely listed, the vocabulary is widely available, and adjacent exposure is easy to present as ownership — which makes resume screening especially weak for this discipline.
In a regulated environment the stakes rise further, because handling of sensitive data is part of the technical requirement rather than a separate compliance workstream.
Calibration: defining what proof would look like
Before sourcing, the evidence standard is written down. For a platform role that typically means pipeline ownership carried into production, how correctness and drift were detected, governance around regulated data, and the measurable business use the work served.
Writing it down is what prevents recruiter interpretation from drifting once outreach accelerates.
SME review: where the model becomes real
A practitioner reviews depth in a live conversation — not an academic exam, but a conversation about decisions, trade-offs and failure modes. The question is whether the candidate can explain what they built, defend why, and describe what happened when it did not work.
This is the step that separates a notebook from a production system, and it cannot be replaced by a keyword match or a longer resume.
Ask what broke, and who fixed it. The answer is the assessment.
Submission: three files with visible trade-offs
The output is a small shortlist where each profile leads on something different — production ownership, domain alignment, stakeholder leadership — with the trade-offs stated rather than hidden.
You can see the structure this produces in the Submission Explorer inside Prism Labs, which walks through three anonymized demonstration profiles built to the same standard.