Risk Analytics Consultant / Assistant Vice President

Wells Fargo is seeking a Risk Analytics Consultant (Assistant Vice President), an individual contributor role requiring 2+ years of experience in the credit risk analytics domain, primarily with credit card and loan products. Individuals in this role will support the Development Team and Risk Business Team. The role is responsible for validating business rules and strategies using various types of testing such as functional testing, user acceptance testing, and regression testing. The role also provides analytics to help improve efficiency and effectiveness.

The ideal candidate will be able to partner with the US team and India team to identify opportunities to optimize the existing process with zero defect leakage in assigned tasks. Additionally, the candidate should be able to understand business requirements for complex business rules.

The role is linked to the Decision Science Strategy Validation team that supports various unsecured consumer lending products, including Cards, Co-Brand, Retail Services, Personal Loans, and Flex Loan. Business policy rules and strategy implementation use decision engines like Zoot Webrule Builder, FICO DMP, Fiserv-ACS/Optis, and Experian PowerCurve. These decision engines help drive acquisition, portfolio management, authorization, and collections risk management decisioning for unsecured lending through rules design, development, and various types of testing. The scope involves supporting all new product launches and BAU releases.

In this role, you will:

• Participate in less complex analysis and modeling initiatives, and identify opportunities for process production, data reconciliation, and model documentation improvements within Risk Management.
• Review and analyze programming models to extract data, and manipulate databases to provide statistical and financial modeling, and exercise independent judgment to guide new and existing projects with medium-risk deliverables.
• Coordinate and consolidate the production of monthly, quarterly, and annual performance reports for more experienced management.
• Present recommendations for resolving data reconciliation, production, and database issues.
• Exercise independent judgment while developing expertise in policy governance, risk projects, and regulatory requests.
• Collaborate and consult with peers, managers, experienced managers, compliance, and various lines of business.

Required Qualifications:

• 2+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.

Desired Qualifications:

• Work with decision systems (Zoot Webrule Builder, FICO DMP, Experian PowerCurve) to implement, validate, and monitor strategies across the unsecured lending lifecycle (Acquisition, Portfolio, Collections).
• Perform end-to-end testing (Unit, SIT, UAT, Regression) and validation using SAS/SQL frameworks to ensure strategy accuracy and system integrity.
• Manage UAT and production deployments, including post-production monitoring, validation, and issue resolution.
• Analyze data flows, source systems (SOR), and Risk DataMarts, ensuring accuracy and alignment with business requirements.
• Develop automation solutions (VB Script, Selenium/UFT, UNIX shell scripting) to improve efficiency and reduce manual effort.
• Participate in Agile processes, contributing to sprint planning, execution, and continuous improvement.
• Provide technical guidance, stakeholder communication, and thought leadership to drive innovation and team effectiveness.

Education & Experience:

• Bachelor's degree in Engineering, Technology, Mathematics, Econometrics, Computer Science, or related fields.
• 2+ years of experience in credit risk analytics (unsecured lending).

Technical Skills:

• Strong hands-on experience with SAS and SQL for data analysis, validation, and testing.
• Experience with data warehouses/databases (Teradata, Oracle, SQL Server, DB2).
• Understanding of testing methodologies, system architecture, and data integration frameworks.
• Exposure to automation tools/scripts (VB Script, Selenium, UFT, UNIX shell scripting).

Domain Knowledge:

• Understanding of credit cards and personal loan lifecycle.
• Knowledge of credit risk strategies, segmentation, scorecards, and decisioning frameworks.
• Familiarity with unsecured lending policies and regulatory considerations.

Good to Have Skills:

• Ability to write and work with Python for data analysis and automation.
• Hands-on exposure to GenAI and Agentic AI use cases, including applying AI-driven solutions in analytics or decisioning workflow.