Wells Fargo is seeking a Senior Risk Analytics Consultant (Assistant Vice President) which is a senior individual contributor role 4+ years of experience in credit risk analytics domain, primarily with Personal Loan products. Individuals in this role will support the development Team, Risk Business Team. Responsibility to validate Business rules/ Strategies using various type of testing like Functional testing, User acceptance testing and Regressions testing. Provide 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, should be able to understand business requirements for complex business rules.

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

Desired Qualifications:

Education & Experience

Bachelor's degree in engineering, Technology, Mathematics, Econometrics, Computer Science, or related fields.
4+ years of experience in credit risk analytics (unsecured lending).
2+ years of experience with decision systems (Zoot, FICO DMP, Experian PowerCurve).

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 testing methodologies, system architecture, and data integration frameworks.
Exposure automation tools/scripts (VB Script, Selenium, UFT, UNIX Shell scripting).

Domain Knowledge

Understanding 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

Job Expectations:

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.

Posting End Date:

28 Jun 2026

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.

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, should be able to understand business requirements for complex business rules.

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

Desired Qualifications:

Education & Experience

Bachelor's degree in engineering, Technology, Mathematics, Econometrics, Computer Science, or related fields.

4+ years of experience in credit risk analytics (unsecured lending).

2+ years of experience with decision systems (Zoot, FICO DMP, Experian PowerCurve).

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 testing methodologies, system architecture, and data integration frameworks.

Exposure automation tools/scripts (VB Script, Selenium, UFT, UNIX Shell scripting).

Domain Knowledge

Understanding 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

Job Expectations:

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.

Senior Risk Analytics Consultant, Senior Assistant Vice President