Senior Lead Risk Analytics Consultant-Card Financial Grounding Forecasting

About the position

About this role: Wells Fargo is seeking a Sr. Lead Risk Analytics Consultant to support the Cards organization with a new account Baseline Financial Grounding forecasts, forecast v. actuals tracking, and updating senior and executive management on the latest new card origination financial returns. This role partners with Product, Finance, and Marketing to deliver accurate forecasts, and optimized customer acquisition performance. In addition, this role serves as the connector between account planning and P&L valuation teams—bringing together multiple financial inputs to create a unified view of new account performance. You will support financial grounding by validating assumptions, reconciling results, and translating complex analytical findings into clear, insight‑driven updates for senior and executive leadership. In this role, you will: Produce recurring card origination Baseline Financial Grounding updates Integrate channel and segment level valuations with the latest new account forecast Produce transparent forecast v. actual reporting to senior management Develop and Maintain Python Financial aggregate model and key inputs. Research forecasting discrepancies and validating forecast inputs.

Responsibilities
• Produce recurring card origination Baseline Financial Grounding updates
• Integrate channel and segment level valuations with the latest new account forecast
• Produce transparent forecast v. actual reporting to senior management
• Develop and Maintain Python Financial aggregate model and key inputs.
• Research forecasting discrepancies and validating forecast inputs.

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

Nice-to-haves
• Experience working with credit card data and analytics, with an understanding of account‑level structures and key business drivers
• Deep understanding of credit card P&L drivers such as acquisition costs, interchange, revolve behavior, loss rates, and funding costs
• Strong background in statistics, economics, or financial valuation with ability to apply both qualitative and quantitative methodologies
• Strong Python experience supporting financial or forecasting models, including updating assumptions and maintaining model components
• Proficiency in SQL and SAS for extracting data, validating inputs, and supporting reconciliation work
• Experience working with valuation frameworks, P&L builds, or new account profitability analysis
• Ability to combine multiple financial inputs (account plans, valuation outputs, and forecast assumptions) into a cohesive financial narrative
• Experience performing forecast‑vs‑actual analysis, including evaluating deltas and identifying root causes
• Strong analytical skills with the ability to pull data, draw insights, and develop recommendations that inform decision‑making
• Strong storytelling and presentation skills, with the ability to build insight‑driven presentations and translate complex data into compelling narratives that influence senior leadership
• Bachelor’s or Master’s degree in a quantitative or technical field

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