Product Manager - Anti Fraud
Job description
Product Manager, Anti-Fraud owns the product roadmap for systems that detect, prevent, and respond to fraud and abuse across the customer lifecycle on a large-scale GPU cloud and AI infrastructure platform. The role balances stopping bad actors with keeping friction near zero for legitimate customers.
At a glance
- Work mode
- Remote
What you'll do
- Own the end-to-end anti-fraud product roadmap: signup/KYC checks, payment fraud detection, account takeover protection, and compute-abuse (e.g., crypto mining, resource reselling) prevention
- Own the rules and risk-scoring surfaces — the tooling that lets analysts and data scientists define, test, and deploy detection rules and ML models with clear guardrails and audit trails
- Own the manual review and case-management experience for the Trust & Safety operations team, including queues, evidence views, and action workflows (block, limit, step-up verification, release)
- Own customer-facing friction points — verification flows, step-up challenges, and appeals — designed to minimize false positives and protect the legitimate user experience
- Identify fraud and abuse incidents early — define the signals, alerts, and thresholds that surface incidents before they scale, and own the detection surface that flags them
- Participate in incident reviews and post-mortems, capturing root causes and turning each finding into concrete improvements to detection rules, models, and the roadmap
- Ensure timely response to active incidents — drive fast triage, clear ownership, and mitigation, working alongside Trust & Safety, Engineering, and Data Science to contain impact
- Write clear PRDs and specs that translate fuzzy risk problems into shippable engineering and data-science work
- Partner with Analytics team on detection models — defining the problem, labels, and success criteria, and deciding where rules vs. ML are the right tool
- Run experiments and monitor rollouts, watching both fraud-catch metrics and false-positive / customer-friction impact
- Work with Legal/Compliance to keep detection and enforcement aligned with payment-network rules, KYC/AML expectations, and data-privacy requirements
- Track and report on fraud loss, chargeback rate, false-positive rate, review throughput, and time-to-detection
What we're looking for
- Proven product management experience in fraud, risk, trust & safety, or payments
- Strong analytical skills — comfortable with data, SQL or equivalent, and reasoning about precision/recall trade-offs and metrics
- Ability to make decisions under ambiguity and to balance security, business, and customer-experience priorities
- Solid collaboration with engineering and data science; you can hold a technical conversation about signals, features, and model behavior
- Exposure to cloud, SaaS, marketplace, fintech, or infrastructure products
- Understanding payment fraud, chargebacks, KYC/AML, or device/network signals (fingerprinting, velocity, IP reputation)
Nice to have
- Familiarity with ML-based detection systems and their operational lifecycle (drift, retraining, monitoring)
- Experience with abuse patterns specific to compute or GPU platforms (mining, credential stuffing, free-tier farming)
Your team
Trust & Safety
Benefits
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
Apply
About Nebius
Leading a new era in cloud infrastructure for the global AI economy
Nebius is building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment. Built by engineers, for engineers, the company owns hard problems across compute, storage, networking and applied AI, from large-scale GPU orchestration to inference optimization.
Mission
Building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Key facts
- 1,500+
- Amsterdam
- AI cloud infrastructure
- Listed on Nasdaq (NBIS)
- Global footprint with R&D hubs across Europe, the UK, North America and Israel
- Team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D
- Runs a large-scale GPU cloud and AI infrastructure platform
What they value
- Fast moving
- Bold thinking
- Constant growth
- Meaningful impact
- Trust and real ownership
- Opportunity to shape the future of AI