Role Overview

We are seeking an experienced Risk & Fraud Product Manager to lead the development of a comprehensive risk & fraud management framework for Delta Exchange. You will work closely with engineering, compliance, operations, and analytics teams to identify vulnerabilities, detect anomalies, and build systems to mitigate trading, transaction, and behavioral risks.

Key Responsibilities

• Design and implement the end-to-end risk and fraud detection framework across trading, payments, onboarding, and user behavior
• Own the risk product roadmap, prioritizing features and capabilities such as anomaly detection, transaction limits, velocity checks, and behavioral monitoring
• Develop tools and systems for real-time fraud detection, suspicious activity alerts, account takeovers, and anti-abuse mechanisms
• Work closely with compliance and operations to align on AML/KYC and regulatory risk guidelines
• Partner with data science and engineering to design and fine-tune fraud detection models and scoring systems
• Establish key risk metrics and dashboards for proactive monitoring and incident management
• Define and document rules engines, thresholds, and triggers for different types of fraud (e.g., wash trading, front-running, bonus abuse)
• Collaborate with finance and payment gateway partners to handle chargebacks, disputes, and recovery mechanisms
  
  

Requirements

• 4-8 years of experience in risk, fraud, or trust & safety product management, preferably in fintech, crypto, or payment companies
• Demonstrated experience building and scaling fraud or risk detection systems from scratch
• Familiarity with crypto trading behaviors, blockchain analytics tools, and fraud vectors specific to crypto ecosystems
• Strong analytical and data skills; ability to interpret risk signals, define metrics, and run experiments
• Solid understanding of regulatory risk, AML/KYC, and compliance best practices
• Strong project management skills with the ability to work cross-functionally in a fast-paced environment
• Bonus: Experience with machine learning models for fraud detection, exchange market surveillance, or decentralized finance (DeFi)