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Senior Fraud Data Analyst
Overview
POSITION OVERVIEW
Fidelity National Financial (FNF) is seeking a Senior Fraud Data Analyst to join the Compliance organization’s Fraud Operations function. This role is responsible for supporting the intake, documentation, and analysis of wire fraud events (both attempted and confirmed) ensuring incidents are captured accurately and consistently to enable downstream analytics, detection, response, and regulatory reporting.
As a key member of the Fraud Operations team, this individual will work cross-functionally with Information Security, Technology, Operations, and business units to manage fraud event intake, correlate signals across multiple systems, identify discrepancies, and support post-incident reviews. The role also helps ensure that insights and lessons learned from incidents are fed back into fraud detection processes, operational controls, and training programs as part of a structured continuous improvement cycle.
The ideal candidate is highly disciplined, detail-oriented, and driven by measurable operational outcomes. Success in this role is demonstrated through improvements in data quality, intake accuracy, fraud detection insights, and operational effectiveness across the fraud lifecycle.
- LOCATION
- This role sits 100% remote.
DUTIES & RESPONSIBILITIES
- Fraud Data Integration & Signal Correlation
- Aggregate, transform, and analyze data from multiple systems including Proofpoint, escrow platforms, banking data, and internal wire-related sources.
- Correlate fraud-related signals across platforms to identify patterns, systemic risks, and emerging threat vectors.
- Maintain consistent taxonomies, metadata standards, and structured analytic methodologies to ensure reliable reporting and analysis.
- Fraud Detection & Intelligence Enablement
- Generate actionable insights that improve fraud monitoring, triage, detection capabilities, and overall fraud threat visibility.
- Identify opportunities to strengthen internal controls and improve the security of the wire instruction lifecycle.
- Partner with Fraud Operations, Compliance, Information Security, and external intelligence sources to enhance detection capabilities and threat intelligence.
- Compliance Reporting & Analytics
- Produce compliance-ready reporting including dashboards, risk exposure reporting, Key Risk Indicators (KRIs), performance indicators, and fraud trend analyses.
- Develop structured reports supporting investigations, regulatory reporting, and audit defensibility.
- Ensure consistent and high-quality metadata to support enterprise-level fraud reporting and lifecycle visibility.
- Operational Enablement & Cross-Functional Collaboration
- Collaborate with Fraud Operations, intake teams, and technology partners to translate analytics into operational improvements.
- Provide analytical insights to support process hardening, system controls, and fraud prevention initiatives.
- Support coordination with external partners including law enforcement, banking institutions, and cyber intelligence organizations.
- MINIMUM REQUIREMENTS
- Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Finance, or a related field, or equivalent combination of education and professional experience.
- 4+ years of experience working with data analytics, data engineering, fraud analysis, financial crime analytics, or similar analytical roles.
- Strong experience working across the full data lifecycle including data preparation, transformation, analysis, and insight generation.
- Proficiency with SQL and modern data analysis tools including Excel, Power Query, Power BI, or similar analytics platforms.
- Ability to design and work with structured and unstructured datasets, ensuring accuracy, normalization, and analytical readiness.
- Demonstrated ability to identify patterns, anomalies, and correlations within large or complex data sets.
- Ability to translate complex data findings into clear, actionable insights for technical and non-technical stakeholders.
- Strong attention to detail and ability to work effectively in high-stakes operational environments.
- PREFERRED EXPERIENCE
- Experience working with fraud analytics, financial crimes, wire fraud, or cyber fraud environments.
- Familiarity with data modeling techniques and scalable data architecture supporting enterprise reporting and analytics.
- Experience leveraging AI or machine learning techniques such as classification, anomaly detection, pattern recognition, or predictive modeling within analytics workflows.
- Experience developing dashboards, operational metrics, and reporting frameworks supporting compliance, risk, or fraud detection programs.
- Experien
