Senior Credit Portfolio Consultant

Wells Fargo•Minneapolis, MN

2d•$87,000 - $154,000•Hybrid

About The Position

About this role: Wells Fargo is seeking a Senior Credit Portfolio Consultant to support Commercial Banking through hands-on oversight of data process and data remediation activities. This role ensures the integrity and accuracy of data across lending systems, supports reporting the data, and acts as a backup across multiple functions. The ideal candidate will be detail-oriented, collaborative, and proactive in identifying and resolving issues. In this role, you will: Oversee and perform daily operations related to: Data Quality (DQ) document collection, including review and remediation requests via DQ Intake Tool Research and remediate data issues and exceptions identified in Enterprise and Commercial Banking level testing activities Streamlined Elastic Workflow Assistant (SEWA) Execute data quality process the ensure policy adherence Resolve moderately complex data issues Drive process improvements and standardization across credit portfolio operations and data governance activities. Assist a team to meet deliverables while leveraging solid understanding of credit products, programs, or related policies Lead projects, teams, or serve as a mentor for less experienced staff Serve as a Data Steward, ensuring data quality, compliance, and remediation across systems of origin and systems of record. Collaborate with Application Business Owners, Data Defect, Control Monitoring to support system changes, enhancements, and ensure accurate reflection of business processes. Participate in system conversion initiatives and User Acceptance Testing (UAT) to validate business requirements. Represent the business in data initiatives, audits, and control reviews.

Requirements

4+ years of Credit Consulting Portfolio experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Nice To Haves

4+ years of Data Process and Remediation or related experience
Strong understanding of Commercial Banking data, particularly across lending systems of origination and systems of record (AFS, Loan IQ, AIMS, LUCAS, CDA/ICMP, nCino, FileNet, InfoLease, CHOICE, others).
Knowledge of risk and regulatory reporting frameworks and requirements.
Knowledge of commercial loan documentation
Strong Excel Skills (Macros, Pivots, VLookup, reconciliation, etc.)
Engineer new data features to enhance in-house datasets, converting manual process into automated or semi-automated process.
Strong collaboration skills with experience partnering with Application Business Owners, data warehouse teams, and business process owners.
Experience mapping manual processes and identifying automation opportunities
Effective communicator with the ability to present findings, influence stakeholders, and advocate for data-driven decision-making.

Responsibilities

Oversee and perform daily operations related to: Data Quality (DQ) document collection, including review and remediation requests via DQ Intake Tool
Research and remediate data issues and exceptions identified in Enterprise and Commercial Banking level testing activities
Streamlined Elastic Workflow Assistant (SEWA)
Execute data quality process the ensure policy adherence
Resolve moderately complex data issues
Drive process improvements and standardization across credit portfolio operations and data governance activities.
Assist a team to meet deliverables while leveraging solid understanding of credit products, programs, or related policies
Lead projects, teams, or serve as a mentor for less experienced staff
Serve as a Data Steward, ensuring data quality, compliance, and remediation across systems of origin and systems of record.
Collaborate with Application Business Owners, Data Defect, Control Monitoring to support system changes, enhancements, and ensure accurate reflection of business processes.
Participate in system conversion initiatives and User Acceptance Testing (UAT) to validate business requirements.
Represent the business in data initiatives, audits, and control reviews.