This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Product Manager – Anti-Fraud based in Spain.
Join an innovative technology environment building large-scale cloud infrastructure that powers the general AI economy. As Product Manager – Anti-Fraud, you will lead the development of products and systems designed to detect, prevent, and respond to fraud across the entire customer lifecycle. From payment fraud and account takeovers to compute abuse and coordinated exploitation, you will tackle complex challenges that directly affect platform security, operational efficiency, and business sustainability. Working at the intersection of Trust & Safety, Payments, Risk, Data Science, and Engineering, you will turn sophisticated risk problems into scalable product solutions. Your mission will be to protect infrastructure and legitimate customers while keeping unnecessary friction to a minimum. This is an opportunity to take meaningful ownership in a fast-moving, international environment where analytical thinking, technical collaboration, and measurable impact are essential.
Accountabilities
Own the anti-fraud product roadmap:
Define and execute the end-to-end strategy for fraud and abuse prevention across customer onboarding, identity verification, payments, account security, and ongoing resource consumption.
Develop fraud detection capabilities:
Lead product initiatives covering stolen payment cards, fraudulent registrations, account takeovers, credential abuse, unauthorized compute usage, cryptocurrency mining, resource reselling, and free-tier exploitation.
Manage risk rules and scoring systems:
Own the tools and workflows that enable analysts and data scientists to define, test, deploy,



and monitor detection rules and machine learning models, with appropriate safeguards and audit trails.
Improve Trust & Safety operations:
Design and optimize manual review and case-management tools, including investigation queues, evidence views, and workflows for blocking accounts, limiting access, requesting additional verification, and releasing legitimate users.
Optimize customer verification experiences:
Develop customer-facing verification, step-up authentication, and appeals processes that reduce false positives while maintaining effective protection against malicious activity.
Strengthen fraud monitoring and incident detection:
Define risk signals, alerting mechanisms, thresholds, and detection workflows to identify emerging incidents early and prevent fraud from escalating.
Lead incident response and continuous improvement:
Coordinate with Trust & Safety, Engineering, and Data Science teams to triage active incidents, establish ownership, mitigate risks, and participate in post-incident reviews.
Translate risk challenges into product solutions:
Write clear product requirements documents (PRDs) and technical specifications that transform ambiguous fraud and abuse problems into actionable engineering and data science deliverables.
Collaborate on detection models:
Partner with Analytics and Data Science teams to define detection problems,



establish data labels and success criteria, and determine when rule-based systems or machine learning approaches are most appropriate.
Run experiments and monitor performance:
Plan experiments, oversee product rollouts, and evaluate detection effectiveness alongside false-positive rates and the impact of security measures on customer experience.
Ensure regulatory and payment compliance:
Collaborate with Legal and Compliance teams to align fraud prevention and enforcement mechanisms with payment-network requirements, KYC/AML obligations, and data privacy standards.
Track and communicate key metrics:
Monitor and report on fraud losses, chargeback rates, false-positive rates, review throughput, and time to detection, using insights to guide prioritization and product improvements.
Requirements
Product management experience:
Proven experience in product management within fraud prevention, risk management, Trust & Safety, payments, or a closely related field.
Strong analytical capabilities:
Comfortable working with data, using SQL or equivalent analytical tools, and interpreting performance metrics to guide product decisions.
Fraud and risk expertise:
Understanding of payment fraud, chargebacks, identity verification, KYC/AML processes, and risk signals such as device fingerprinting, transaction velocity, IP reputation, and network behavior.
Technical product knowledge:
Ability to collaborate effectively with Engineering and Data Science teams and engage in technical discussions about detection signals, data features, system behavior, and model performance.
Data-driven decision-making:
Familiarity with precision and recall trade-offs, detection effectiveness, false-po

📌 Product Manager (Ibiza)
🏢 Jobgether
📍 Ibiza