Monitoring Specialist

You will be responsible for analyzing merchant transaction data to detect suspicious, fraudulent, or anomalous behavior patterns. Collaborating with data science teams to build and refine anomaly detection algorithms using machine learning and statistical methods will be a key aspect of your role. You will also be required to perform deep dives on flagged transactions to identify root causes and patterns. Working closely with risk, product, compliance, and engineering teams to define detection strategies and enhance risk scoring systems will be part of your responsibilities. Furthermore, you will need to maintain and improve the transaction monitoring system, including rule tuning and false positive reduction. Ensuring timely escalation and reporting of suspicious activity to compliance and regulatory bodies as required (e.g., SARs/STRs) will also be essential. Conducting post-incident analysis to improve detection capabilities and reduce future risk is another aspect of this role. Additionally, you will be expected to prepare periodic reports and dashboards for senior management and regulatory reporting. To qualify for this position, you should have a Bachelor's or Master's degree in finance, Data Science, Statistics, Computer Science, or a related field. You must have a minimum of 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 are required. Experience with rule-based and machine learning-based anomaly detection systems is necessary. Familiarity with merchant behavior analytics, risk profiling, and fraud typologies is essential. An understanding of AML (Anti-Money Laundering), KYC, and regulatory requirements is also crucial. Excellent communication and documentation skills are expected in this role.,