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Staff Data Analyst

Pubblicato il 28-10-2026 - Qonto in Milano

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot , based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture (here)(

Our journey:

Founded in 2017 by ( Alexandre )( and ( Steve )( , Qonto has grown to 1,700 Qontoers serving over 750,000 customers across 8 European countries. We have been profitable since 2023, and we are just getting started.

Our beliefs:

We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. ( We've built a discrimination-free hiring process )( the best teams are built on merit.

AI at Qonto:

AI is deeply embedded in how we work ( (here)( )
- Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. -----------------------------------------------------------------------------------------------------
- Join us as a Staff Data Analyst
- Compliance to build the analytics foundations that power Qonto's compliance execution. You'll own a brand-new scope — monitoring KYC/KYB funnels, remediation campaigns, and financial exposure — working cross-functionally with Product, Ops, Risk & Compliance, and Internal Control,



under the guidance of Alma, our Lead Data Analyst.

‍‍‍ As a Data Analyst at Qonto, you will

Build compliance process monitoring from scratch: You'll build and own the data infrastructure that powers compliance monitoring at Qonto — from onboarding funnel analytics to remediation financial exposure — giving product, operations and compliance teams the self-service tools they need to make decisions without waiting on a data request. Model and transform data with dbt: With the collaboration of Analytics Engineer Team, you'll build end-to-end transformation pipelines from source to consumption layer, keeping metric definitions clean and trusted by non-technical stakeholders. Turn regulatory questions into self-service assets: You'll partner with Product, Ops, Risk & Compliance, and Internal Control to scope and ship analytical tools Own the KYC/KYB funnel analytics end-to-end: You'll deliver insights from CS initiation through KYB validation — refusal reasons, document gaps, lead-time distributions — so teams can act on friction fast. Track remediation campaigns and financial exposure: You'll measure MRR secured, at risk,



or lost across active campaigns, with peak intensity in Q4 (budget season) and May–June (reforecast).

❓ What you can expect

A greenfield, strategically critical scope: Qonto is under close regulatory scrutiny — you'll build analytics foundations that matter company-wide, not just for your team. Senior, cross-functional exposure from day one: Product, Ops, Risk & Compliance, Internal Control — few DA roles give you this breadth of senior stakeholder access at this level. Real ownership in the Modern Data Stack: You'll build in Omni and dbt with a high degree of autonomy — no legacy to untangle, just foundations to create. A team where AI is a first-class tool: Unlimited access to AI tools (Claude, Cursor, and more) to evolve how you work, not just output more.

→ Your future manager

Your manager will be (Alma)( our Lead Data Analyst for Ops & Finance. Alma knows exactly what it takes to build an analytics function that actually changes decisions, and she'll push you to do the same. Alma reports to (Erwan)( Director of Business Analytics who oversees the entire Analytics function and ensures alignment across teams.

❓ About You

Compliance or regulated environment

experience:
You've worked analytically on KYC/KYB, AML, remediation, or similar regulatory/operational processes — and you know how to get credible with those stakeholders fast. Self-service product mindset: You've designed dashboards and models for end-users to explore autonomously, adapting the same dataset from

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