Senior Lead Analytics Consultant - Global Employee Fraud Monitoring
About This Role
Wells Fargo is seeking a Senior Lead Analytics Consultant to join the Global Employee Fraud Monitoring Strategies (GEFMS) team. This role provides strategic leadership for the design, governance, and enhancement of enterprise employee fraud detection capabilities. The position is responsible for shaping internal fraud proactive monitoring, driving enterprise-wide internal fraud risk coverage, and ensuring effective, sustainable controls across the organization.
Responsibilities
Lead the strategy, design, development, and implementation of enterprise internal fraud detection rules
Drive the evolution of proactive monitoring by identifying emerging threats, assessing control gaps, and recommending rule enhancements to improve risk coverage and detection effectiveness
Execute and oversee monitoring controls to ensure consistent and effective fraud detection
Translate complex business, operational, and control requirements into scalable analytical solutions that balance risk mitigation and operational efficiency
Influence and partner with senior business leaders, Risk, Compliance, Audit, Technology, and control functions to drive implementation of monitoring solutions and control improvements
Provide leadership and guidance on highly complex analytical initiatives, serving as a key consultant and escalation point for fraud detection strategy and monitoring decisions
Operate with a high degree of independence, exercising sound judgment in managing priorities, resolving ambiguous issues, and making risk-based recommendations to senior leadership
Support governance, documentation, and audit readiness for fraud monitoring activities
Qualifications
7+ 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
4+ years of hands-on experience with SAS and SQL, supporting data-driven rule development for fraud monitoring or identification of out-of-pattern or anomalous activity across large enterprise data sets
Desired Qualifications
Deep knowledge of internal fraud risk management, employee fraud typologies, and proactive monitoring strategies
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 in 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
Location
- 2850 S Price Road - Chandler, AZ
- 1525 W WT Harris Blvd - Charlotte, NC
- 2200 Concord Pike - Wilmington, DE