Senior Data Analyst
K2 Integrity New York, États-UnisSenior Data Analyst
K2 Integrity New York, États-Unis
Senior Data Analyst
Job description
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.
Job requirements
Job responsibilities
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.
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
- 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 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
Job responsibilities
- Design new AML monitoring scenarios or detection models from concept through implementation.
- Conduct lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews
- Leverage SQL and Alteryx to perform forensic transaction analysis and identify previously unknown financial crime risks
- Identify and evaluate transaction networks, customer relationships, and behavioral patterns to uncover previously unidentified financial crime risks
- Utilize statistical analysis, anomaly detection techniques, behavioral profiling, and risk-based segmentation methodologies
- Provide supporting data analytics and documentation for SAR narratives, AML investigations, and regulatory responses
Référence 17630434-07a6-4236-af17-a9f2930cb78b
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