Description review

1st Product Manager

Ooak Data · Paris, Île-de-France, FR · back to the listing

HR standards

48/100

poor

Title ↔ description

83/100

solid

Reads as

Product Manager

100% confident

What this role officially is

ICT product manager — ESCO, the EU occupation classification

ICT product managers analyse and define current and target status for ICT products, services or solutions. They estimate the cost effectiveness, points of risk, opportunities, strengths and weaknesses of products or services provided. ICT product managers create structured plans and establish time scales and milestones, ensuring optimisation of activities and resources.

Also known as: IT product manager, IT products manager, ICT product managers, ICT products manager, ICT products managers

How others title the same work

Large employers

  • Staff Product Manager, Search Experiences Mozilla
  • Missionforce - Senior Product Manager, Agentforce Public Sector Salesforce
  • Product Lead, Connect Stripe
  • Product Manager - Compliance, Bridge Stripe
  • Product Manager, Ecosystem Risk Stripe

Startups

  • Technical Product Manager Careforce
  • Product Manager Agave
  • Product Manager AlgoTest
  • Product Manager Aqua
  • Product Manager Artisan

What the listing never says

  • 16 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

The company

Ooak Data turns company data into training data for AI agents.

Frontier labs can train models to reason. They cannot train them to work: navigating a real company's Slack threads, half-finished Notion docs, contradictory Jira tickets, and permission boundaries. That requires real enterprise data, and you cannot synthesize it. You have to source it.

We plug into enterprise tools, anonymize everything into a structurally identical digital twin, and generate reinforcement-learning environments with expert-level tasks calibrated against frontier models.

We are a Y Combinator company with 7 figures signed contracts with three frontier AI labs, and we are scaling delivery aggressively over the next twelve months. Three founders, full-time since December 2025: Pierre-Louis (CEO, ex-COO in edtech, sold data to frontier labs), Grégoire (CPO, first PM & head of Ops at Epsor through Series B), Thomas (CTO, ex-Head of Data at PayLead, ex-Samsung AI lab).

Why this role exists

Our engineering team ships faster than founders can specify. We have four product surfaces, most of them internal, all of them technical, and every one of them decides whether an environment ships this week or next.

We are hiring our first Product Manager to own the product: what gets built, in what order, and whether it actually made us faster.

What you will own

The full chain, from the moment a CEO agrees to share their data to the moment a frontier lab receives an environment.

Partner experience

• The Data Hub, onboarding and export tutorials a CEO sees when they hand us their company's history. Trust and speed at the top of the funnel.

The data pipeline

• Connectors, ingestion and anonymisation. How raw Slack, Drive, mail and CRM exports become a clean digital twin. You will spend a lot of time with Thomas (CTO) here.

Pharos, our delivery platform

• The internal tool our Ops team lives in to run QA and delivery. Throughput is the metric. This is where 3 env a week becomes 10.

RL environments

• The thing the labs buy. Task design, calibration, what separates a dataset from a real agent training ground.

You will run two kinds of work at once: short projects that need tight coordination across Tech, Ops and GTM this week, and long ones where nothing exists yet and you get to decide what should.

Who you are

•
A doer. You know the product methodologies and you use them when they help, not by the book. Your instinct when something is slow is to fix it, not to schedule a workshop about it.

•
AI-pilled. You vibe code. You prototype before you write a spec. You design your own mockups. You are curious about how the models themselves are built and trained.

•
UX taste, ROI brain. Our workflows have to be brutally efficient. You judge a piece of software or a workflow by efficient it allows us to be or what value it brings to our customers.

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You keep pace. Our engineers ship a lot. You turn that into something coherent rather than slowing it down.

•
7+ years in product, at least some of it technical: data, infra, ML, developer tools or ops platforms. Founders and first PMs who built the function from nothing are very welcome.

•
Fluent French and English. Our customers are American, our data partners spread worldwide, our team speaks both.

• Based in Paris.

The extra that make the difference

• A research streak: you read papers, you have opinions on RL, you have trained or fine-tuned something.

Terms

•
Compensation: €70-90k + bonus, and 0.2% to 0.5% BSPCE depending on profile.

•
Location: Paris Morning Laffitte, on-site with 1 to 2 days WFH.

•
Start date: as soon as you can.

•
Perks: Alan health insurance, 50% Navigo.

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 16 points (from 64 before penalties). Reviewed 21 Sep 2026.