Fraud & FinCrime Data Analyst
Core
Technical analyst owning the rules framework, KPIs, and activity tracking for fraud and financial crime detection in a fintech payments environment.
Role type
Senior IC fraud and financial crime data analyst
Builds
Fraud and AML/TF detection rules, KPI dashboards, and automated analysis pipelines
Domain
Fintech, Payments, Financial Crime (Fraud/AML)
Required skills
Fraud typologies, AML/TF concepts, SQL, Python, distributed data processing (Spark), BI tools (Looker/Tableau/Power BI), rule-based detection design, payment methods knowledge (cards, tokenization, 3DS)
Preferred skills
Rules engines/decisioning platforms, anomaly detection (statistical/ML), financial crime operations experience, auditor/regulator interaction
Technologies
SQL, Python, Spark, Looker, Tableau, Power BI, 3DS, AVS
Responsibilities
Design, build, test, tune, and retire fraud/AML detection rules; define and maintain KPIs for detection effectiveness and false positives; build dashboards for rule changes and team throughput; analyze transaction data to spot anomalies and emerging attack patterns; automate manual analysis and reporting; collaborate with Product, Compliance, Network, and Operations to align on detection and regulatory requirements.
Seniority
Senior, hands-on IC