About the Role
You will lead the development and evolution of Transak's in-house proprietary risk engine, working closely with engineering, data science, operations, and compliance to define and execute the roadmap for fraud detection and risk mitigation at scale. You will own the risk and fraud prevention stack for payment processing, translating evolving fraud typologies into product requirements, working directly with data to analyze incident trends and monitor live risk signals, and architecting the full lifecycle of risk logic including rule management, model integration, and case enrichment. You will also lead vendor selection for third-party risk intelligence tools and collaborate with Risk Operations to build case management and alerting systems that maximize analyst efficiency.
Requirements
- 6-8+ years of Product Management experience, with at least 2 years in risk or fraud-related domains within fintech or crypto
- Deep understanding of fraud vectors in crypto on/off ramps, payment processing, or financial infrastructure
- Strong SQL skills; experience exploring raw datasets, building metrics dashboards, and validating system behavior independently
- Solid foundation in statistics and ML evaluation metrics relevant to fraud detection
- Proven track record of working with data scientists, risk engineers, and fraud ops teams to ship high-impact products
- Experience working with or building rule engines, decision platforms, and/or real-time scoring systems
- Prior exposure to compliance-oriented product design, including KYC/AML, transaction monitoring, and alerts review
- Familiarity with tools such as Alloy, Sardine, Elliptic, Sift, or similar vendors
- Background in scripting (Python etc.) for deeper data exploration or prototyping
- Experience in user-facing risk UX like transaction friction, user appeals, or dynamic KYC workflows
- Understanding of global regulatory environments impacting crypto or fintech fraud handling
Responsibilities
- Own and evolve the product roadmap for the risk engine and fraud detection systems
- Translate evolving fraud typologies into product requirements and technical capabilities
- Collaborate with stakeholders across Compliance, Engineering, Data, and Operations to align on risk product vision
- Own metrics around fraud and chargebacks, false positives, and conversion rates
- Write and optimize DB queries, analyze incident trends, and monitor live risk signals
- Define, track, and report key performance metrics including precision, recall, FPR/TPR, AUC, and latency benchmarks
- Partner with risk engineers and analysts to design statistically sound experiments, calibrate thresholds, and evaluate detection effectiveness
- Architect the full lifecycle of risk logic including rule management, model integration, case enrichment, and outcomes logging
- Lead vendor selection and negotiations for third-party risk intelligence tools, behavioral analytics, and identity verification partners
- Collaborate with Risk Operations to develop case management and alerting systems
- Prioritize internal tooling improvements that enable fast triage, investigation, and override workflows
- Ensure all risk-related features are scalable, testable, and maintainable under real-world loads