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Senior Analytics Manager - Global Employee Fraud Monitoring Detection Analytics
United States, Chandler · Job Posted May 16, 2026
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Job Description
Wells Fargo is seeking a Senior Analytics Manager to join the Global Employee Fraud Monitoring Detection Analytics (GEFMDA) team. This role is responsible for leading and overseeing development of enterprise-level internal fraud proactive monitoring strategies, with accountability for analytical quality, prioritization, and delivery. The Senior Analytics Manager partners directly with executives, senior leaders, and cross-functional risk teams to assess internal fraud events, identify emerging employee fraud risk patterns, and strengthen proactive monitoring capabilities across the enterprise. This role operates in a highly complex, fast-paced environment and requires strong people leadership, deep internal fraud domain expertise, sound analytical judgment, and executive-level communication skills. The successful candidate will ensure monitoring solutions delivered by the team are credible, defensible, well-governed, and able to withstand executive, regulatory, and audit scrutiny, while effectively managing capacity, priorities, and evolving risk demands.
Job Responsibility
Lead, develop, and oversee a team of analytics professionals, providing direction, coaching, performance management, and workload prioritization
Provide managerial oversight for the design, enhancement, and governance of proactive internal fraud monitoring strategies, ensuring alignment with enterprise risk objectives
Establish and enforce consistent analytical standards, documentation, and governance practices across internal fraud analytics
Review and guide the use of SAS- and SQL-based analytics to ensure accurate analysis of large, complex enterprise data sets supporting fraud detection and monitoring
Partner with executives and senior stakeholders to prioritize and deliver high-risk, enterprise-level initiatives with material operational and regulatory impact
Translate complex business, risk, and control requirements into scalable analytical solutions, ensuring effective risk mitigation outcomes
Serve as a trusted advisor and escalation point for senior leadership on internal fraud risk trends, monitoring effectiveness, and control gaps
Work independently with Internal Risk Management (IRM), Control, Audit, and other partners to provide oversight, challenge, and thought leadership on internal fraud risk and control enhancements
Navigate ambiguity and shifting priorities while maintaining strong execution discipline, governance, and accountability
Requirements
7+ years of Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
3+ years of management or leadership experience
3+ years of hands-on experience with SAS and SQL, supporting fraud analytics, monitoring, and reporting across large enterprise data sets
Nice to have
3+ years of experience in an analytics leadership or people-management role, including responsibility for prioritization, quality oversight, and team development
Deep knowledge of employee misconduct risks, including internal fraud typologies and behavioral indicators
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
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 analytics and monitoring solutions that withstand audit and regulatory review while achieving measurable risk reduction
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