Transaction Monitoring Analyst

Job Description

Role & responsibilities: Design and implement transaction monitoring rules and models for merchant financing and payments. Analyze merchant transaction data to detect suspicious, fraudulent, or anomalous behavior patterns. Collaborate with data science teams to build and refine anomaly detection algorithms using machine learning and statistical methods. Perform deep dives on flagged transactions to identify root causes and patterns. Work closely with risk, product, compliance, and engineering teams to define detection strategies and enhance risk scoring systems. Maintain and improve the transaction monitoring system, including rule tuning and false positive reduction. Ensure timely escalation and reporting of suspicious activity to compliance and regulatory bodies as required (e.g., SARs/STRs). Conduct post-incident analysis to improve detection capabilities and reduce future risk. Prepare periodic reports and dashboards for senior management and regulatory reporting. Preferred candidate profile : Required Qualifications Bachelors or master’s degree in finance, Data Science, Statistics, Computer Science, or related field. 7+ years of experience in transaction monitoring, fraud analytics, or anomaly detection in financial services, preferably in merchant/acquirer finance. Strong analytical skills with hands-on experience in SQL, Python or other analytical tools. Experience with rule-based and machine learning-based anomaly detection systems. Familiarity with merchant behavior analytics, risk profiling, and fraud typologies. Understanding of AML (Anti-Money Laundering), KYC, and regulatory requirements. Excellent communication and documentation skills.