Data Quality Specialist

✅ Your missions

As Data Quality Specialist, you are the last line between a dataset and a frontier AI lab. Nothing ships without passing your bar.

You sit inside the tech team, embedded with the engineers who build the ingestion and anonymization pipeline, and you work every day alongside the Ops team who run the deliveries. You report to Grégoire (COO & co-founder).

This is a hands-on, individual contributor role. You own the quality function itself, not a team.

Define the standard. Acceptance criteria, checklists, sampling methods, error thresholds. Today they barely exist. You write them, and you make them stick. Audit what we ship. Processed and anonymized data, reviewed before delivery: PII leakage, replacement consistency, structural integrity, and whether the business value survived the anonymization. Automate your own job. Manual review does not scale. You write the detection scripts and the analyses yourself, and you work with the engineers to turn the ones that prove themselves into production checks, so the obvious errors never reach a human again. Measure and escalate. Quality metrics per dataset and per vendor, including the third parties we work with. You track them, you surface the problems, and you drive them to resolution. Translate client requirements into specs. Work with the tech and sales teams to turn what a lab actually wants into concrete, testable quality criteria. Close the loop with engineering. You are the person who tells the pipeline team what is broken upstream, with the evidence to back it. Quality problems get fixed at the source, not patched at delivery.