Sr. Manager, Decision Science – Valuation Analytics, Unsecured Lending

Wells Fargo Bank•Wilmington, DE

2d•Hybrid

About The Position

Wells Fargo is seeking a Sr. Decision Science Manager to lead the development, governance, and continuous enhancement of financial valuation models and supporting tools for Branded Cards, Co‑Brand Cards, Small Business Card, and Personal Lending portfolios. This role sits at the intersection of advanced analytics, financial valuation, and risk governance, driving enterprise decision-making through state-of-the-art modeling frameworks built in Python. The leader will oversee model lifecycle management—from design through governance approval—and ensure models remain accurate, compliant, and aligned with evolving business and economic inputs.

Requirements

Advanced proficiency in Python
Experience with large-scale data processing and model optimization
Experience with statistical / ML modeling techniques
Experience with SQL, cloud or distributed compute environments (preferred)
Strong understanding of cash flow–based valuation models and NPV frameworks
Hands-on experience working with Model Risk Management frameworks, including model approval and validation cycles, documentation and audit readiness, ongoing monitoring and annual reviews
Strong understanding of consumer lending economics: Capital, Pricing, margins, cost of funds, credit losses, customer behavior
Ability to translate complex analytics into strategic recommendations and quantified financial impact (e.g., NPV, ROA, margin uplift)
Demonstrated leadership in managing teams or influencing cross-functional stakeholders
Demonstrated leadership in driving adoption of new tools and methodologies
7+ years of Risk 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

Nice To Haves

7+ years of experience in valuation modeling and risk analytics within a data-driven or financial services environment
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
Deep experience in credit cards, unsecured lending, or personal lending portfolios
Proven track record of owning and delivering financial valuations or forecasting models
Combines deep technical expertise (Python, modeling) with strong financial and business judgment
Operates effectively in regulated environments, balancing innovation with governance rigor
Acts as a bridge between analytics, technology, and business strategy
Drives measurable impact through, improved valuation accuracy, faster model deployment cycles, enhanced decision quality across portfolios

Responsibilities

Own end-to-end lifecycle of financial valuation models (design, development, validation support, implementation, monitoring).
Lead migration and development of scalable valuation frameworks in Python-based environments.
Incorporate key financial drivers including: Unit cost structures, Corporate treasury rates / cost of funds, Behavioral, credit, and macroeconomic assumptions.
Oversee models that support card & loan origination, line increase, pricing, business development and portfolio management strategies.
Serve as primary interface with Model Risk Management (MRM) partners to secure model approvals and validations, support annual reviews and ongoing monitoring, maintain high-quality documentation and controls, and ensure adherence to enterprise model governance standards across the entire model lifecycle (development, validation, implementation, monitoring).
Deliver valuation tools and analytical capabilities to partner teams across Branded Cards, Co‑Brand Cards, Credit Cards, and Personal Lending.
Standardize and productionize modeling frameworks to enable consistent, scalable decisioning across portfolios.
Act as a technical thought leader, driving adoption of modern data, tooling, and modeling practices.
Identify and deploy emerging AI/ML capabilities to improve model performance, automation, and scalability.
Promote use of vectorized computation, scalable architectures, and model optimization techniques.
Continuously benchmark and enhance modeling approaches to maintain best-in-class valuation capabilities.
Partner with Finance, Treasury, Risk, Product, and Strategy teams to align valuation frameworks with financial planning assumptions.
Translate analytics into clear, decision-ready insights.
Present model outputs, sensitivities, and trade-offs in executive forums and governance committees.