Staff Product Manager Ai Products Expertise
Hace 7 días
España
Qonto
Jornada completa
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Our Mission and CustomersWe are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools.
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 JourneyFounded in ***
* by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; Staff Product Manager – DataJoin us as a Staff Product Manager – Data to enhance Qonto's customer experience through innovative ML solutions. You'll drive the maturity and scalability of our ML capabilities, addressing concrete business problems while fostering innovation.
You will work closely with Daniele Garbarino, our VP Data, to support ML product developments that significantly impact our 600,000+ customers' financial management experience.
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, and Cashflow Management — 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.
Continuously improve through data: monitor and analyze the performance of ML models and products, making data-driven recommendations to raise the bar.
What We're Looking ForProduct management experience with a data/ML focus: you have proven experience in product management, with concrete examples of ML or data products you took from 0 to 1 or significantly scaled. 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.
What We Can Offer YouDomain being reshaped by AI: ML is transforming financial services — from expense categorization to cashflow forecasting. Squad autonomy as the default: you own your roadmap and ship without red tape. 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 ManagerYou will report to Daniele, VP Data, who brings deep expertise in scaling data organizations at high?Daniele is passionate about building data?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.
* by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; Staff Product Manager – DataJoin us as a Staff Product Manager – Data to enhance Qonto's customer experience through innovative ML solutions. You'll drive the maturity and scalability of our ML capabilities, addressing concrete business problems while fostering innovation.
You will work closely with Daniele Garbarino, our VP Data, to support ML product developments that significantly impact our 600,000+ customers' financial management experience.
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, and Cashflow Management — 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.
Continuously improve through data: monitor and analyze the performance of ML models and products, making data-driven recommendations to raise the bar.
What We're Looking ForProduct management experience with a data/ML focus: you have proven experience in product management, with concrete examples of ML or data products you took from 0 to 1 or significantly scaled. 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.
What We Can Offer YouDomain being reshaped by AI: ML is transforming financial services — from expense categorization to cashflow forecasting. Squad autonomy as the default: you own your roadmap and ship without red tape. 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 ManagerYou will report to Daniele, VP Data, who brings deep expertise in scaling data organizations at high?Daniele is passionate about building data?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.