Description
We are seeking a Senior Product Manager to lead our Anti-Money Laundering (AML) detection product within Identity & Risk Intelligence.
As a Senior Product Manager, you will lead the build and scaling of Machine Learning models, rules and risk signals that detect financial crimes across Adyen's products, markets and customer base.
Key responsibilities include:
- Risk Detection & ML Modeling: Lead the build and scaling of Machine Learning models, rules and risk signals that detect financial crimes across Adyen's products, markets and customer base.
- Scalable, Self-Service Detection: Move financial crime detection toward a self-service framework that picks up new typologies quickly, using ML, GenAI and agentic approaches to reduce manual effort and keep pace with Adyen's growth without adding headcount.
- Strategy Execution & Prioritization: Own the execution of the financial crime detection strategy. Prioritize ruthlessly, make data-driven trade-offs, and stop or descope work when the evidence shows it is not worth pursuing.
- Compliance & Regulatory Partnership: Act as the main product partner for Compliance. Translate regulatory expectations into clear product boundaries, agree how the team delivers within them, and demonstrate continuous improvement to regulators.
- Performance & Effectiveness: Define how detection quality and efficiency are measured in a domain where the ground truth is often unknown, and continuously improve signal quality for our Investigations team.
- Cross-Functional Leadership: Lead a team of Data Scientists, Data Analysts and Backend Engineers alongside your engineering lead, and keep Compliance, Operations, and other risk teams aligned on the roadmap.
Requirements:
- Experience: 8+ years of Product Management experience building ML-driven, high-scale products in fast-growing tech or fintech environments. 2+ years of experience in AML, fraud detection or financial crime.
- ML Product Expertise: Proven track record of owning and scaling ML-driven products such as detection, scoring or risk models. Comfortable going deep with Data Scientists on model performance, evaluation and trade-offs.
- Regulated Environment: Experience building products in highly regulated environments such as payments, banking or fintech, with a solid understanding of how regulation shapes product decisions.
- Stakeholder Management: Strong influence with senior and opinionated stakeholders, especially Compliance, Legal and Risk. Able to hold a position, explain the reasoning and keep their trust.
- Decision-Making: Clear, data-driven trade-offs and the confidence to say no. Comfortable owning outcomes without a single clean success metric.
- Ownership: Highly autonomous and accountable, able to take an agreed strategy and drive it through execution.