Senior Analyst, Fraud Prevention & Investigations

Walmart•Bentonville, AR

19h•Hybrid

About The Position

The Senior Analyst, Fraud Prevention & Investigations is a hybrid individual contributor responsible for both data-driven fraud detection and hands-on field investigations across the Spark Driver platform. This role combines advanced analytics — behavioral analysis, signal development, anomaly detection — with real-world investigative work including on-site observation at stores, evidence collection, and witness engagement. The ideal candidate thrives in ambiguous problem spaces, thinks like an adversary, and moves fluidly between a data terminal and a store parking lot. One day may involve building fraud-detection queries and refining signal thresholds; the next may require conducting on-site surveillance, gathering physical evidence, or coordinating with local law enforcement. This role is the critical bridge between digital fraud signals and on-the-ground operational reality. Senior Analysts translate complex behavioral patterns into actionable insights and defensible decisions, contributing to both the analytical models that detect fraud and the investigative processes that resolve it.

Requirements

Bachelor’s degree in Criminal Justice, Data Analytics, Business, Information Systems, Security, or related field and 3+ years’ experience in fraud detection, investigations, risk analysis, or compliance — OR 5+ years’ equivalent experience without a degree.
Experience across BOTH data-driven fraud detection (SQL, analytics, pattern identification) AND field-based investigations (on-site observation, evidence collection, case documentation).
Proficiency in SQL and advanced Excel for large-scale data analysis, anomaly detection, and pattern identification.
Demonstrated experience with structured investigation processes, evidence-handling standards, chain of custody, and audit-ready case file management.
Strong analytical and critical thinking skills with the ability to interpret complex, mixed-signal data and draw defensible conclusions.
Ability to work independently in both the field and at a desk, exercising sound judgment in dynamic situations.
Valid driver’s license and ability to travel regionally (up to 50-60% of the time) for field investigation assignments.
Effective written and verbal communication skills; able to distill complex findings into clear reports for cross-functional audiences.

Nice To Haves

Experience in gig economy, marketplace, or platform fraud-detection and investigation operations.
Experience with OSINT techniques, device forensics, geolocation analysis, or identity-verification processes.
Prior law enforcement, military investigations, or corporate security investigation experience.
Background in behavioral analytics, segmentation, or statistical pattern recognition applied to fraud or risk scenarios.
Professional certifications such as CFE (Certified Fraud Examiner), CAMS, CPP, or equivalent.
Familiarity with fraud-detection platforms, case management systems, or rules-engine tools.

Responsibilities

Analyze user behavior and platform interaction patterns to identify unusual activity, suspicious accounts, and emerging fraud vectors at scale.
Apply core analytics fundamentals — segmentation, trend analysis, anomaly detection, correlation testing — to uncover fraud patterns across large datasets.
Interpret mixed signals by combining data points such as GPS movement, device details, metadata, and behavioral indicators to assess risk.
Apply real-world context from field experience to inform and improve data-driven detection, considering cultural, social, and environmental factors that automated systems might miss.
Build and refine fraud indicators — measurable behaviors, thresholds, and composite signals that can be monitored through dashboards and automated models.
Identify motivations and opportunities for fraud; translate hypotheses into testable data signals and validation frameworks.
Stress-test queries by enumerating legitimate scenarios, then refine logic, thresholds, and exclusion rules to minimize false positives.
Provide structured feedback and business requirements that support new fraud-signal development or detection-tool enhancements.
Conduct on-site investigations into suspected fraud, account integrity violations, identity misuse, and policy non-compliance at delivery locations, driver staging areas, stores, and partner sites.
Gather, preserve, and document physical and digital evidence including photographs, video (CCTV), witness statements, device data, and operational records in accordance with evidence-handling standards.
Validate or refute digital fraud signals through on-the-ground observation, interviews, and real-world context assessment.
Coordinate with local law enforcement, regulatory agencies, or legal counsel when investigations escalate or require external engagement.
Follow a structured investigation process, documenting each step clearly from initial detection through final decision with audit-ready case files.
Produce clear, defensible investigation reports summarizing methodology, evidence (both digital and physical), findings, and recommended actions.
Use open-source research (OSINT) to look beyond internal data, confirm identities, and uncover external fraud clues or coordinated networks.
Track and report on investigation outcomes, resolution rates, and patterns identified through both analytical and field activities.
Present operational insights to Product, Legal, Compliance, Engineering, and Care Operations to inform tooling improvements and policy updates.
Identify geographic, temporal, and behavioral patterns from field investigation data that indicate emerging fraud trends or systemic risks.
Provide field-sourced intelligence to inform signal design, model refinement, and broader fraud-prevention strategy.
Support training and knowledge-sharing by documenting investigation best practices, case studies, and lessons learned.