In this role, you will:
- Lead or participate in moderately complex initiatives, and delivering insight and decision strategies within analytics and reporting, and contribute to large-scale planning related to Risk Analytics
- Review and analyze moderately complex data aggregation, forecasting, reporting, and programming models
- Be responsible for process production, data reconciliation, and model documentation in alignment with policy governance
- Resolve data, production, business modeling, and lead team to meet Risk Analytics deliverables while leveraging solid understanding of risk reporting policies, modeling strategies, procedures, regulatory requests, and compliance requirements
- Collaborate and consult with peers, experienced managers, compliance, and technology to resolve modeling, forecasting, and production issues, and achieve analytic and reporting goals
- Lead projects, teams, and mentor less experienced staff
- Partner with cross enterprise risk analysts in development of common modeling strategies
Required Qualifications:
- 4+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Required Qualifications for Europe, Middle East & Africa only:
- Experience in Risk Analytics, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Desired Qualifications:
- 4+ years of experience SQL, Teradata, and or Hadoop experience.
- 4+ years of experience with BI tools such as Tableau, Power BI or Alteryx applications.
- 3+ years of experience in risk (includes compliance, financial crimes, operational, audit, legal, credit risk, market risk).
- Experience researching and resolving data problems and working with technology teams on remediation of data issues.
- Demonstrated strong analytical skills with high attention to detail and accuracy.
- Excellent verbal, written, and listening communication skills.
Job Expectations:
- Participate in complex initiatives related to business analysis and modeling, including those that are cross functional, with broad impact, and act as key participant in data aggregation and monitoring for Risk Analytics.
- Fully understands Data Quality Checks, Methodology, Dimensions for data completeness, accuracy, and that policies and procedures are followed.
- Becomes a SME in the DQ Check elements, technology infrastructure utilized, and fully understands the metadata and lineage from DQ report to source data.
- Escalates potential risks, issues, or calendar/timeliness risks in a timely manner to management/Data Management Sharepoint.
- Ensures the organization and storage of DQ checks artifacts, files, and evidences are effective, efficient, and make sense.
- Perform deep dive analytics (both Adhoc and structured) and provide reporting or results to both internal and external stakeholders.
- Design and build rich data visualizations to communicate complex ideas and automate reporting and controls.
- Create and interpret Business Intelligence data (Reporting, Basic Analytics, Predictive Analytics and Prescriptive Analytics) combined with business knowledge to draw supportable conclusions about current and future risk levels.
- Becomes a SME in the Reporting, Data Quality check elements, technology infrastructure utilized, and fully understands the metadata and lineage from DQ report to source data.
- To demonstrate the ability to identify and implement areas of opportunities for quality assurance, data validation, analytics and data aggregation to improve overall reporting efficiencies.
- Creating and executing the UAT test cases, logging the defects and managing the defects till closure.
- Collaborate and consult with peers, less experienced to more experienced managers, to resolve production, project, and regulatory issues, and achieve risk analysts, and common modeling goals
28 Apr 2025
Wells Fargo Recruitment and Hiring Requirements:
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.