Regulatory submissions and GxP compliance specialist
Here's what AI can do for this role — and what still needs a human. Built straight from ENSEK's own job advert, running live on my_db.fisher_demo.regulatory_submissions. Not a slide about AI. The job, getting done.
Every line on the left is lifted from ENSEK's actual job ad. If a card lacks a harvested JD line, it is omitted. On the right is the AI doing it — with eligible cards running live against the warehouse and offline inspection clearly labelled in the workspace.
“submission pipeline by type and authority — workload overview for regulatory cycle planning.”
What does the regulatory submission pipeline look like by type and authority — the workload overview the team runs at the start of every review cycle?
bar chart“overdue submissions by risk level — RCSA-style prioritisation matrix for regulatory team triage.”
Which overdue submissions carry the highest risk level — the RCSA-style prioritisation matrix for workload triage?
deviation“CAPA closure rate trend — regulatory health score and inspection-readiness KPI across product families.”
What is the CAPA closure rate trend across product families — the regulatory health score the team tracks as an inspection-readiness KPI?
table“21 CFR Part 11 / Annex 11 compliance gaps across product lines — data integrity risk matrix.”
Where are the 21 CFR Part 11 and EU Annex 11 compliance gaps across product lines — the data integrity risk matrix?
table“change control cycle time by change type — efficiency signal for regulatory strategy: is Minor vs Major classification accurate?”
What is the change control cycle time by change type — the efficiency signal for regulatory strategy (Minor vs Major classification)?
tableThe honest other half. AI does the analysis; a person owns the decision — especially where regulation, fairness and accountability bite.
A plain-English question — the same one the job ad describes — is translated to SQL by the agentic backend.
Curated cards run server-side against MotherDuck when eligible. The workspace separately labels any local inspection path.
Runs against my_db.fisher_demo.regulatory_submissions. No synthetic numbers.
Each figure carries a falsifier — recomputed from the result set, not a stored number, so it can't quietly drift.
It's the role getting done: curated questions run live server-side against the warehouse; local inspection is labelled inside the workspace.
Open the live workspace →Provenance. Offline path: SYNTHESISED labelled 1,500-row regulatory submission pipeline dataset (ITS-169, seed 20260614). Schema mirrors my_db.fisher_demo.regulatory_submissions. MHRA/FDA/EMA context; 21 CFR Part 11 and EU Annex 11 compliance markers. NOT real regulatory data. Live path (dormant): server-side MotherDuck query against fisher_demo.regulatory_submissions.
It's Sorted — I took ENSEK's job ads and didn't write a report on what AI could do. I built it. Get the rest sorted →
I'm trained on this proof and the real ENSEK: the Ignition meter-to-cash platform (seven modules), the move under Centrica in 2024, 7M+ energy accounts migrated for suppliers like British Gas and Utility Warehouse, and the Ofgem framing. Ask me how the Data Analyst function changes shape, or which open roles map to which Ignition module.