{"schemaVersion":"jobsearcher.job.v1","id":"ea7916723fbc015df4a641b8","url":"https://jobsearcher.com/jobs/ea7916723fbc015df4a641b8","canonicalUrl":"https://jobsearcher.com/jobs/ea7916723fbc015df4a641b8","title":"Senior Data Analyst","description":"Job description\nWe 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.\nJob requirements\nAdvanced degree in a related field (e.g., Data Science, Statistics, Finance)\n5+ 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\nDemonstrated ability to identify suspicious behaviors, emerging typologies, hidden relationships, and anomalous transaction patterns through exploratory data analysis\nExperience developing, enhancing, and validating AML detection strategies, scenarios, models, or monitoring rules based on forensic review of transactional activity\nStrong 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\nProven ability to transform investigative findings into defensible detection logic, thresholds, and risk indicators.\nAdvanced SQL skills with the ability to independently query, extract, manipulate, and analyze large datasets to uncover suspicious activity patterns and support detection model development\nStrong Alteryx experience, including workflow design, data preparation, aggregation, segmentation, statistical analysis, and investigative data exploration across large transaction populations\nAbility to independently formulate hypotheses, test suspicious activity indicators, and develop evidence-based recommendations for detection enhancements\nStrong communication skills with the ability to articulate complex analytical findings\nExperience designing new AML monitoring scenarios or detection models from concept through implementation preferred\nExperience conducting lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews preferred\nExperience leveraging SQL and Alteryx to perform forensic transaction analysis and identify previously unknown financial crime risks preferred\nFamiliarity with SAR narratives, AML investigations, regulatory expectations, and suspicious activity identification preferred\nExperience evaluating transaction networks, customer relationships, and behavioral patterns to uncover previously unidentified financial crime risks preferred\nKnowledge of statistical analysis, anomaly detection techniques, behavioral profiling, and risk-based segmentation methodologies preferred\nJob responsibilities\nDesign new AML monitoring scenarios or detection models from concept through implementation.\nConduct lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews\nLeverage SQL and Alteryx to perform forensic transaction analysis and identify previously unknown financial crime risks\nIdentify and evaluate transaction networks, customer relationships, and behavioral patterns to uncover previously unidentified financial crime risks\nUtilize statistical analysis, anomaly detection techniques, behavioral profiling, and risk-based segmentation methodologies\nProvide supporting data analytics and documentation for SAR narratives, AML investigations, and regulatory responses","company":"K2 Integrity","rawCompany":"k2 integrity","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-06T15:07:43.943Z","occupations":[{"code":"33-3021.06","title":"Intelligence Analysts","slug":"intelligence-analysts"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"13-2099.04","title":"Fraud Examiners, Investigators and Analysts","slug":"fraud-examiners-investigators-and-analysts"}],"industries":[{"code":"561611","title":"Investigation and Personal Background Check Services","slug":"investigation-and-personal-background-check-services"},{"code":"522320","title":"Financial Transactions Processing, Reserve, and Clearinghouse Activities","slug":"financial-transactions-processing-reserve-and-clearinghouse-activities"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Data Analyst","description":"Job description\nWe 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.\nJob requirements\nAdvanced degree in a related field (e.g., Data Science, Statistics, Finance)\n5+ 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\nDemonstrated ability to identify suspicious behaviors, emerging typologies, hidden relationships, and anomalous transaction patterns through exploratory data analysis\nExperience developing, enhancing, and validating AML detection strategies, scenarios, models, or monitoring rules based on forensic review of transactional activity\nStrong 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\nProven ability to transform investigative findings into defensible detection logic, thresholds, and risk indicators.\nAdvanced SQL skills with the ability to independently query, extract, manipulate, and analyze large datasets to uncover suspicious activity patterns and support detection model development\nStrong Alteryx experience, including workflow design, data preparation, aggregation, segmentation, statistical analysis, and investigative data exploration across large transaction populations\nAbility to independently formulate hypotheses, test suspicious activity indicators, and develop evidence-based recommendations for detection enhancements\nStrong communication skills with the ability to articulate complex analytical findings\nExperience designing new AML monitoring scenarios or detection models from concept through implementation preferred\nExperience conducting lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews preferred\nExperience leveraging SQL and Alteryx to perform forensic transaction analysis and identify previously unknown financial crime risks preferred\nFamiliarity with SAR narratives, AML investigations, regulatory expectations, and suspicious activity identification preferred\nExperience evaluating transaction networks, customer relationships, and behavioral patterns to uncover previously unidentified financial crime risks preferred\nKnowledge of statistical analysis, anomaly detection techniques, behavioral profiling, and risk-based segmentation methodologies preferred\nJob responsibilities\nDesign new AML monitoring scenarios or detection models from concept through implementation.\nConduct lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews\nLeverage SQL and Alteryx to perform forensic transaction analysis and identify previously unknown financial crime risks\nIdentify and evaluate transaction networks, customer relationships, and behavioral patterns to uncover previously unidentified financial crime risks\nUtilize statistical analysis, anomaly detection techniques, behavioral profiling, and risk-based segmentation methodologies\nProvide supporting data analytics and documentation for SAR narratives, AML investigations, and regulatory responses","datePosted":"2026-08-06T15:07:43.943Z","dateModified":"2026-08-06T15:07:43.943Z","hiringOrganization":{"@type":"Organization","name":"K2 Integrity","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ea7916723fbc015df4a641b8"},"url":"https://jobsearcher.com/jobs/ea7916723fbc015df4a641b8"}}