Staff Product Manager [Machine Learning expertise]

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 because 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 Machine Learning Product Manager to enhance Qonto's customer experience through innovative solutions. You'll drive the maturity and scalability of our ML/AI capabilities, addressing concrete business problems while fostering innovation. ➡️ What you'll do Own the ML product roadmap end-to-end: Define what we build, why, and in what order — gathering insights from engineering, data science, and business teams to develop a prioritized strategy that addresses real customer needs. Drive key ML product initiatives: Lead the definition and design of ML solutions for products like Attachment Matcher, Transaction Categorizer — from discovery through delivery. Collaborate across the full stack: Work with data scientists, engineers, and business stakeholders to ensure successful implementation of ML capabilities that drive measurable business value. Own your decisions and communicate them clearly: Articulate the rationale behind priorities and engage key stakeholders — including customers, product, and executive teams. Continuously improve through data: Monitor and analyze the performance of models and products, making data-driven recommendations to raise the bar. ➡️ What we're looking for Product management experience with an ML focus: You have proven experience in product management, with concrete examples of ML products you significantly scaled. You think in outcomes, not features. Technical fluency in ML: You have a solid grasp of machine learning concepts and applications, allowing you to collaborate effectively with technical teams and translate complex ideas into product requirements. Strong stakeholder management: You excel at building relationships with diverse stakeholders and communicating complex technical concepts to non-technical audiences. Analytical thinking: You make data-driven decisions that balance customer needs with business objectives — and you're comfortable with hard trade-offs. Strategic vision: You can develop a compelling product vision and roadmap that aligns with company goals and delivers measurable impact. ➡️ What we can offer you A domain being reshaped by AI: ML is transforming financial services — from expense categorization to cashflow forecasting. You'll build products at the frontier of what's possible, not maintain existing ones. Squad autonomy as the default: You own your roadmap and ship without red tape. No approval chains, no waiting on committees. Real impact at scale: Your work will directly affect how 600,000+ SMEs manage their finances every day. Cross-functional collaboration: You'll sit at the intersection of product, data science, and engineering — with a team that values craft and moves fast. ➡️ About your future manager You'll work closely with Sophie , Manager of the AI Lab. Sophie has led cross-functional teams through the full product lifecycle at both fast-growing startups and established tech companies. She partners directly with Product and Tech leadership to align the AI roadmap with Qonto's strategic goals. Her approach: give engineers real ownership, create space for experimentation, and empower the squad to adapt their ways of working in pursuit of real impact. At Qonto, we understand that true diversity isn’t just about ticking boxes on a hiring checklist. Apply regardless of the boxes you tick — who knows? You may have the missing piece of the puzzle we’ve been searching for all along. By applying, you agree that Qonto processes your personal data to assess your application. Your data is kept for up to 2 years in our candidate pool. Read our Privacy Notice for full details. - --------------------------------- ---------------------------------- ---------------------------------- On average, our hiring process lasts 20 working days . More information on our candidate journey here ---------------------------------- ---------------------------------- ---------------------------------- 🔒 Your security matters to us Recruitment scams are on the rise. Keep in mind, w e will never work with third-party platforms or agencies that request payment from candidates. If you receive a suspicious message claiming to be from Qonto, please report it right away ( support@qonto.com )