Data Analyst, Fraud Data & Analytics

Jobtailor; Arizona; On-site; USD 130,000 - 170,000; Full time

Job summary

Vanguard is seeking a senior fraud analytics leader to drive end-to-end analytics initiatives, from problem definition through monitoring and governance. You will design offline detections, establish performance metrics, and translate complex insights for executive audiences, while coaching analysts and collaborating with investigative teams.

The role requires a strong background in fraud, analytics validation, and data quality, with experience in cloud environments and enterprise data assets.

Qualifications

• Minimum of five years related work experience.
• Advanced SQL skills and Python or similar language.
• Experience developing dashboards in Tableau.
• Knowledge of financial-services fraud typologies preferred.

Responsibilities

• Lead complex fraud analytics initiatives from problem definition to monitoring.
• Design, develop, back-test, and optimize offline fraud detections.
• Establish performance measures for detections and reporting.
• Identify emerging fraud trends, anomalous behavior, and fraud signatures.
• Lead forensic analysis and analytical support for significant fraud incidents.
• Develop and own executive reporting, dashboards, and loss reporting.
• Define data quality controls and validate data used in reporting and detection.
• Document methodologies, data lineage, and control procedures for governance.
• Translate analytical findings into concise recommendations for leadership.
• Review peer work and coach less-experienced analysts.
• Partner with investigative teams to improve detection effectiveness.

Skills

Advanced SQL Skills

Python Programming

Dashboard Development

Fraud Detection Optimization

Analytical Validation Methods

Education

Undergraduate degree

Tools

Tableau

Cloud Platforms

Job description

• Lead complex fraud analytics initiatives from problem definition and data assessment through implementation, measurement, and ongoing monitoring
• Design, develop, back-test, and optimize offline fraud detections that generate actionable leads for investigative teams
• Establish performance measures for detections, including precision, recall, false-positive rates, alert volumes, loss exposure, and prevented or avoided impact
• Identify emerging fraud trends, anomalous behavior, common attributes, and fraud signatures across account, client, transactional, and case data
• Lead forensic analysis and analytical support for significant fraud incidents, control gaps, and emerging typologies
• Develop and own executive reporting, dashboards, benchmarking, loss reporting, and recurring fraud performance products
• Define data quality controls and validate the completeness, accuracy, and reasonableness of fraud data used in reporting and detection
• Document analytical methodologies, assumptions, data lineage, and control procedures to support governance and audit readiness
• Translate complex analytical findings into concise recommendations for fraud operations, risk partners, technology teams, and senior leadership
• Review analytical approaches and work products developed by other analysts and provide technical direction, coaching, and quality assurance
• Partner with investigative teams to establish feedback loops and disposition processes that improve detection effectiveness
• Serve as an analytical subject-matter expert on cross-functional fraud initiatives, data modernization efforts, and evaluation of fraud tools or capabilities

Requirements

• Minimum of five years related work experience
• Undergraduate degree or equivalent combination of training and experience
• 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
• Vanguard is not offering visa sponsorship for this position

Core Competencies

Demonstrates expertise in leading complex fraud analytics initiatives, including the design and optimization of fraud detection methods, performance measurement, and executive reporting. Proficient in translating analytical findings into actionable recommendations for diverse audiences while ensuring data quality and governance.

Highest-signal resume keywords

• Advanced SQL Skills
• Python Programming
• Dashboard Development in Tableau
• Fraud Detection Optimization
• Analytical Validation Methods

Hard Skills

• Fraud Analytics
• Data Assessment
• Performance Measurement
• Anomaly Detection
• Statistical Analysis
• Data Quality Controls
• Analytical Methodologies
• Fraud Loss Measurement
• Risk Rules Development
• Executive Reporting

Soft Skills

• Influencing Business Decisions
• Coaching Analysts
• Translating Technical Findings
• Collaboration with Investigative Teams
• Quality Assurance

Industry Keywords

• Financial-Services Fraud Typologies
• Fraud Operations
• Fraud Investigations
• Fraud Performance Products
• Data Modernization Efforts

Tools & Technologies

• Tableau
• Cloud-Based Data Environments
• Governed Enterprise Data Assets