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Corporate Risk helps all Wells Fargo businesses identify and manage risk. The team focuses on several key risk types, including conduct, credit, financial crimes, information security, interest rate, liquidity, market, model, operational, regulatory compliance, reputation, strategic, and technology risk. The group provides leadership, enhances communications, assists with problem identification and solutions, and shares best practices. In addition, the group provides an enterprise-wide view of risk, assists management and our Board of Directors in identifying and monitoring risks that may affect multiple lines of business, and takes appropriate action when business activities exceed the risk tolerance of the company.
The Credit and PPNR (CaPM) Model Development Team (the 'team') is a unit within Corporate Credit and is responsible for model development and implementation of the following model types: I. Pre-Provision Net Revenue (PPNR) estimates, including forecasting models, to support stress-testing under the Comprehensive Capital Analysis and Reporting exercises (CCAR) and nine-quarter business forecasting. II. Credit loss estimation models for the entire loan portfolio to support allowance for credit loss, stress testing, and Basel.
The team is seeking a dynamic individual with experience in predictive modeling and data analysis to join the model development team focusing on PPNR model development for non-interest income, expense, and recovery/resolution models. The team is responsible for developing, documenting and supporting models and results. The selected candidate will be able to identify areas of model weakness and strengths and help identify practical solutions within the constraints of the bank's information systems. They will perform this role across 30 plus models. In doing so, the selected candidate will become an expert in the relevant bank data systems and the General Ledger. An ability and willingness to support the work of other modelers is expected, as is the strategic acumen to understand model performance across a variety of economic and business strategy contexts. The candidate must be able to bridge the gap between theory and practice to deliver solutions and conclusions suitable for the intended business purpose – stress testing, business forecasting, and recovery/resolution planning.
Our ideal candidate will have a sound background and understanding of PPNR modeling, including a strong understanding of modeling techniques like OLS and generalized linear models including logistic regression, hazard models, time-series, and panel regression. The same candidate would be able to bridge between parametric approaches to analysis and machine learning techniques. She/he will appreciate the use of modeling approaches such as penalized regression, spline-fitting, or spectral analysis and how they relate to models built using piecewise regression or some other extension of the linear model tradition.
Ideally, this individual will also have experience and knowledge with the components of bank income statements including trading gains and losses. The selected candidate will be comfortable extracting data across a variety of data sources and databases. SQL knowledge is expected. An ability and willingness to work environments as disparate as Essbase SmartView and Linux grids using SAS and/or PySpark is the desired end-state.
The duties of this position will include, but not be limited to the following:
Creating and maintaining an ongoing modeling strategic assessment with regular monthly updates.
Document models to forecast conditional results indicative of both Wells Fargo and industry level performance
Work closely with line of business partners to develop and enhance the theory and business logic behind the models and forecasts; address data and address questions from our partners, model validation, and governance.
Data research to facilitate modeling and analysis
Coherently articulate analysis results to her/his manager, business partners, model validation, audit, and governance
Support ad hoc analytic projects
2+ years of experience in an advanced scientific or mathematical field
A master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science
A PhD in a quantitative discipline
Excellent verbal, written, and interpersonal communication skills
Other Desired Qualifications
SAS, SQL, and Python programming skills for data extraction and analysis
A solid background in both statistical theory and applications
Knowledge of time-series regression and forecasting models
Experience implementing and coding large and complex models
Knowledge of bank products across consumer, wholesale, and trust and investment
Detail oriented, results driven, and has the ability to navigate in a quickly changing and highly demanding environment while balancing multiple priorities
Understanding of bank regulatory data sets and other industry data sources
A willingness to take a lead role on projects, while functioning effectively as an individual contributor.
An understanding of the importance of, and the ability to manage to, deadlines in an environment where there are multiple dependencies on the outcome of one's work is essential.
All offers for employment with Wells Fargo are contingent upon the candidate having successfully completed a criminal background check. Wells Fargo will consider qualified candidates with criminal histories in a manner consistent with the requirements of applicable local, state and Federal law, including Section 19 of the Federal Deposit Insurance Act.
Relevant military experience is considered for veterans and transitioning service men and women. Wells Fargo is an Affirmative Action and Equal Opportunity Employer, Minority/Female/Disabled/Veteran/Gender Identity/Sexual Orientation.
Internal Number: 5549579-3
About Wells Fargo
Wells Fargo & Company (NYSE: WFC) is a diversified, community-based financial services company with $1.9 trillion in assets. Wells Fargo’s vision is to satisfy our customers’ financial needs and help them succeed financially. Founded in 1852 and headquartered in San Francisco, Wells Fargo provides banking, investment and mortgage products and services, as well as consumer and commercial finance, through 7,400 locations, more than 13,000 ATMs, the internet (wellsfargo.com) and mobile banking, and has offices in 32 countries and territories to support customers who conduct business in the global economy. With approximately 260,000 team members, Wells Fargo serves one in three households in the United States. Wells Fargo & Company was ranked No. 29 on Fortune’s 2019 rankings of America’s largest corporations. News, insights and perspectives from Wells Fargo are also available at Wells Fargo Stories.
www.wellsfargo.com | Twitter: @WellsFargo