Risk Control Principal Product Specialist

About Us

Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance.   Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution.   Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. Role Overview Own the full lifecycle of our fiat risk control products, covering fraud prevention and AML across high-frequency fiat deposit, withdrawal, and payment flows. The focus is on the underlying risk mechanisms: how transactions are screened, scored, held, and released in real time. Combine risk insight with business needs to plan, design, iterate, and optimize an efficient, intelligent risk control system that protects the platform without adding unnecessary user friction.   Key Responsibilities

1. Risk Mechanism & Product Design

• Own the roadmap for fiat and payment risk control systems, including transaction monitoring and fraud detection
• Design and iterate on core mechanisms such as rule engines, decision flows, risk tiering, holds and releases, and automated interdiction
• Define the logic behind risk parameters (limits, velocity thresholds, triggers, escalation paths) and balance risk coverage against user friction

1. High-Frequency Transaction Risk

• Design controls that operate under high concurrency and strict latency requirements across fiat on/off-ramp, card acquiring, card issuing, and payment transaction risk control
• Work with Engineering on real-time data pipelines, rule execution performance, fallback and degradation strategies, and stability under peak load
• Detect and close gaps around abnormal patterns such as velocity abuse, account takeover, card fraud, chargebacks, mule accounts, and structuring

1. AI-Powered Risk Control Capabilities

• Use AI to improve user conversion rates and reduce blockers in risk control flows
• Optimize risk-related communications delivered to customers during transactions
• Use AI to proactively guide users through document submission and identity verification, helping them resolve account restrictions or blocks imposed by risk controls

1. Requirement Analysis & Product Planning

• Explore risk control requirements across business scenarios; combine industry trends and company strategy to set long-term plans and short-term iteration goals
• Produce high-quality PRDs that define functionality, performance, security, and other standards

1. Delivery & Cross-functional Collaboration

• Lead prototype design and implementation; coordinate Technology, Data, Compliance, and Operations to deliver on time and at quality
• Communicate the value and usage guidelines of risk products, answer questions, and ensure risk strategies are implemented effectively across business lines
• Translate AML requirements into product capabilities, including transaction monitoring scenarios, sanctions and watchlist screening, and suspicious activity workflows
• Support audit and regulatory inquiries with clear documentation of risk logic

1. Data Analysis & Optimization

• Continuously monitor product data and evaluate the effectiveness of risk strategies and product features
• Define metrics (false positive rate, interception rate, fraud loss rate, case handling time, decision latency) and drive data-based iteration
• Run back-testing and A/B validation before rule or model rollout
• Build feedback loops between case management, operations, and strategy tuning; support incident handling, root cause analysis, and post-incident reviews

  Requirements

• Bachelor's degree or above in Computer Science, Mathematics, Stati

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