The role involves analyzing large financial datasets to identify suspicious behavioral patterns and emerging AML typologies. The analyst will design detection models, optimize SQL queries, and develop Power BI dashboards to enhance financial crime monitoring.
We are seeking a forensic analytics professional who is naturally curious, investigative, and hypothesis-driven. The successful candidate will be comfortable working directly with datasets containing millions of records, using SQL and Alteryx to explore data and uncover hidden behavioral patterns. They should demonstrate a proven ability to move beyond predefined requirements and independently discover emerging AML typologies, develop defensible detection logic, and enhance the organization's financial crime monitoring capabilities. This contractor position is a remote role in the USA.
Advanced degree in a related field (e.g., Data Science, Statistics, Finance)
5+ years of experience working with large datasets containing millions of records to analyze large-scale transactional, customer, or financial datasets in support of AML, financial crimes, fraud, or investigative analytics initiatives
Demonstrated ability to identify suspicious behaviors, emerging typologies, hidden relationships, and anomalous transaction patterns through exploratory data analysis
Experience developing, enhancing, and validating AML detection strategies, scenarios, models, or monitoring rules based on forensic review of transactional activity
Strong understanding of money laundering methodologies, including structuring, layering, funnel accounts, mule activity, third-party transfers, rapid movement of funds, high-risk counterparties, and other financial crime typologies
Proven ability to transform investigative findings into defensible detection logic, thresholds, and risk indicators.
Advanced SQL skills with the ability to independently query, extract, manipulate, and analyze large datasets to uncover suspicious activity patterns and support detection model development
Strong Alteryx experience, including workflow design, data preparation, aggregation, segmentation, statistical analysis, and investigative data exploration across large transaction populations
Ability to independently formulate hypotheses, test suspicious activity indicators, and develop evidence-based recommendations for detection enhancements
Strong communication skills with the ability to articulate complex analytical findings
Experience designing new AML monitoring scenarios or detection models from concept through implementation preferred
Experience leveraging SQL and Alteryx to perform forensic transaction analysis and identify previously unknown financial crime risks preferred
Familiarity with SAR narratives, AML investigations, regulatory expectations, and suspicious activity identification preferred
Experience evaluating transaction networks, customer relationships, and behavioral patterns to uncover previously unidentified financial crime risks preferred
Knowledge of statistical analysis, anomaly detection techniques, behavioral profiling, and risk-based segmentation methodologies preferred
Analyze transactions, accounts, customer profiles, alerts, and third-party data to identify suspicious patterns, anomalies, and emerging risks
Write and optimize complex SQL queries and Python scripts to extract, manipulate, and analyze large financial datasets hands-on
Design and implement financial crime detection models, scenarios, and rule sets tailored to AML typologies
Conduct root cause analyses on financial crime incidents to improve detection accuracy and prevention strategies
Build and maintain ETL pipelines to ingest, clean, and validate data from multiple sources
Develop clear, compelling dashboards and reports in Power BI to support investigator decision-making and stakeholder reporting
Apply AI/ML techniques including supervised and unsupervised models, anomaly detection, and NLP — to enhance detection efficiency and surface emerging risks
Leverage graph analytics to map and analyze relationships between entities, accounts, and transactions
Translate forensic data analyses into findings and recommendations that enable effective, timely investigations
Mentor junior analysts and contribute to building overall team capability
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