Responsibilities:

• Leads complex fraud analytics initiatives from problem definition and data assessment through implementation, measurement, and ongoing monitoring.
• Designs, develops, back-tests, and optimizes offline fraud detections that generate actionable leads for investigative teams.
• Establishes performance measures for detections, including precision, recall, false-positive rates, alert volumes, loss exposure, and prevented or avoided impact.
• Identifies emerging fraud trends, anomalous behavior, common attributes, and fraud signatures across account, client, transactional, and case data.
• Leads forensic analysis and analytical support for significant fraud incidents, control gaps, and emerging typologies.
• Develops and owns executive reporting, dashboards, benchmarking, loss reporting, and recurring fraud performance products.
• Defines data quality controls and validates the completeness, accuracy, and reasonableness of fraud data used in reporting and detection.
• Documents analytical methodologies, assumptions, data lineage, and control procedures to support governance and audit readiness.
• Translates complex analytical findings into concise recommendations for fraud operations, risk partners, technology teams, and senior leadership.
• Reviews analytical approaches and work products developed by other analysts and provides technical direction, coaching, and quality assurance.
• Partners with investigative teams to establish feedback loops and disposition processes that improve detection effectiveness.
• Serves as an analytical subject-matter expert on cross-functional fraud initiatives, data modernization efforts, and evaluation of fraud tools or capabilities.

Qualifications

• Minimum of five years of progressively responsible experience in data analytics, fraud analytics, risk analytics, or a related field.
• Demonstrated experience independently leading complex analytical initiatives and influencing business decisions.
• Advanced SQL skills, including experience analyzing large and complex datasets.
• Proficiency in Python or another analytical programming language used for data preparation, automation, statistical analysis, or detection development.
• Advanced experience developing dashboards and executive reporting in Tableau or a comparable visualization platform.
• Experience developing, testing, monitoring, or optimizing fraud detections, risk rules, anomaly-detection methods, or analytical models.
• Strong understanding of analytical validation methods, data quality controls, and performance measurement.
• Ability to translate technical findings into concise, actionable recommendations for technical and non-technical audiences.
• Demonstrated ability to review peer work, establish analytical standards, and coach less-experienced analysts.
• Knowledge of financial-services fraud typologies, investigations, fraud operations, or fraud loss measurement strongly preferred.
• Experience working in cloud-based data environments and with governed enterprise data assets preferred.
• Undergraduate degree or equivalent combination of training and experience; graduate degree preferred.

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.