Senior Data Analyst

Job Responsibilities

• 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

Job Requirements

• 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
• 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
• 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 conducting lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews 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