Fraud Rule Engineer

The Fraud Rules Engineer will support the Safety Team by designing, implementing, testing, and maintaining fraud detection rules within a proprietary internal rule engine. This role requires strong foundational programming skills and the ability to translate fraud strategies, business logic, and analytical insights into clear, efficient rules that prevent account‑level fraud. Key Responsibilities • Develop, implement, and deploy fraud detection rules in the internal rule engine. • Translate fraud strategies and business requirements into structured rule logic. • Monitor rule performance and tune/optimize logic to improve detection while minimizing customer impact. • Test rules and perform performance analysis throughout the rule lifecycle. • Document all rules, logic changes, and updates according to governance standards. • Utilize SQL to evaluate rule performance and analyze supporting data. • Follow structured change‑management and governance processes for rule deployment. • Collaborate with the Logic Strategy Team to translate fraud scenarios into rule‑based countermeasures. Required Qualifications • Experience with declarative rule writing; Drools knowledge is a must • Strong foundational programming skills (more technical than a data analyst). • Experience developing or maintaining rule‑based logic systems. • Proficiency with SQL, including writing and optimizing complex queries. • Familiarity with Java‑based environments and JVM concepts. • Experience in fraud prevention such as identity fraud, account takeover, onboarding risk, or application risk. • Experience with performance testing, rule evaluation, and tuning. • Ability to balance rule effectiveness with customer experience considerations. • Experience working within structured change‑management or governance frameworks (preferred). • Comfort working within virtualized environments. • Ability to understand object‑oriented concepts (e.g., classes), though production Java coding is not required. • Understanding of rule‑engine logic patterns and high‑performance rule construction. • Working knowledge of Git, including branching, merging, and managing updates to a central rule repository. • Demonstrated analytical aptitude or prior experience developing fraud detection logic. Fraud Scenarios You Will Work On • Account takeover detection • Identity‑related fraud • Sign‑up and onboarding risk • Application scoring for financial products • (This role is not focused on credit‑card transaction fraud.) Tools & Environment • Proprietary internal rule engine (JVM‑based, GUI-driven, heavily customized). • Access to existing rule sets for reference. • Use of SQL and internal data tools for testing and performance evaluation. • Examples of expected logic: • “For every login attempt, check if the IP address originates from a prohibited country. If yes, block the attempt.”