Data Quality Specialist

🔍 Who we're looking for

* 4+ years in data quality, data operations, or QA, ideally at a data labeling company, a data provider, or an AI company.
* Hands-on with large, messy datasets: processing them, auditing them, finding what is wrong with them. Python and SQL are required: you write your own scripts to interrogate a dataset, you do not wait for someone to pull the data for you.
* Comfortable in a tech team. You will sit with engineers, read their pipeline, and hold your own in a technical conversation. You are not expected to ship production code, but you are expected to be credible.
* A track record of building quality standards from scratch, not just applying someone else's checklist.
* Obsessive attention to detail. You enjoy finding the error everyone else missed, and you are not satisfied until you understand why it was there.
* Systems thinking. When you find one error, your instinct is to ask how many others like it exist and how to catch them automatically.
* AI-first. You use LLMs and AI tools as daily leverage to audit, automate, and move faster.
* Fluent English, mandatory (working language with our partners and the labs).
The extras that make the difference
* Familiarity with PII, de-identification, or privacy requirements.
* Exposure to annotation quality concepts: rubrics, inter-annotator agreement, guideline design.
* Understanding of how training data is actually used: SFT, RLHF, RL environments, evaluation.
* Experience working with external vendors or an annotation workforce.

🎁 Why join us

* A function to build, not to inherit. Quality at Ooak Data is yours to define from the ground up.
* Your work is visible. What you validate goes straight to the largest AI labs in the world.
* Entrepreneurial adventure: founding impact, live the early days of an ambitious company at the front line of the AI revolution.
* Backed by Y Combinator, join just as we accelerate.
* Offices in central Paris.
* Perks: Alan health insurance (mutuelle), 50% Navigo covered.