Lead Analytic Consultant - Global Employee Fraud Monitoring Strategies

Wells Fargo is seeking a Lead Analytic Consultant to join the Global Employee Fraud Monitoring Strategies (GEFMS) team. This role focuses on designing and implementing enterprise proactive monitoring rules to detect internal fraud, including ownership of rule development, control execution, and ongoing strategy maintenance.

Responsibilities

• Design, develop, and implement internal fraud detection rules to support enterprise proactive monitoring
• Maintain and enhance fraud monitoring strategies to address evolving risks and business priorities
• Execute and oversee monitoring controls to ensure consistent and effective fraud detection
• Leverage SAS and SQL to analyze large, complex data sets and support rule development and performance evaluation
• Translate business and control requirements into practical analytical solutions and rule logic
• Partner with stakeholders and cross-functional teams to implement monitoring solutions and drive control improvements
• Evaluate rule performance and recommend enhancements to improve detection effectiveness and coverage
• Support governance, documentation, and audit readiness for fraud monitoring activities
• Operate with independence in managing deliverables, prioritizing work, and resolving analytical challenges

Requirements

• 5+ years of Analytics, Reporting, Financial Modeling, or Statistics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 3+ years of hands-on experience with SAS and SQL, supporting data-driven rule development for fraud monitoring or identification of anomalous or out-of-pattern activity across large enterprise data sets

Qualifications

• Deep domain expertise in employee misconduct and conduct risk typologies, including behavioral indicators and emerging fraud patterns
• Demonstrated experience designing and implementing rule-based detection strategies to identify potential fraud or out-of-pattern or anomalous activity
• Experience leveraging large, complex datasets to build proactive monitoring solutions that identify potential fraud signals
• Experience overseeing advanced analytics techniques, including statistical modeling, machine learning, and rule-based detection approaches
• Experience operating within large, complex data environments with disparate data sources, systems, and database structures
• Quantitative educational background (e.g., Statistics, Economics, Mathematics) with extensive applied analytics experience
• Experience integrating and analyzing human resources, allegation, and business application data to develop holistic fraud risk insights and inform predictive monitoring strategies
• Strong familiarity with the allegation lifecycle, including intake, sensitive matters, internal investigations, root cause analysis, and customer impact considerations
• Strong executive communication skills, with the ability to clearly articulate analytical insights, risks, and recommendations to leadership, audit, and regulatory audiences
• Proven track record delivering fraud detection and monitoring solutions that are defensible and withstand regulatory and audit review
• Experience managing work in ambiguous, fast-changing environments with competing priorities and regulatory expectations
• Familiarity with Python or additional analytics tools is preferred to support automation and analytical efficiency
• Working knowledge of advanced analytics techniques, including supervised and unsupervised machine learning and natural language processing

Schedule

Hybrid work schedule - three (3) days in office & two (2) days remote.

Location: 1525 W WT Harris Blvd Charlotte, NC or 2200 Concord Pike, Wilmington, DE