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At Wells Fargo, we are looking for talented people who will put our customers at the center of everything we do. We are seeking candidates who embrace diversity, equity and inclusion in a workplace where everyone feels valued and inspired.
Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.
As the company's second line of defense, Corporate Risk — or Independent Risk Management — provides independent oversight of risk-taking activities. Independent Risk Management establishes and maintains Wells Fargo's risk management program and provides oversight, including challenges to and independent assessment of, the frontline's execution of its risk management responsibilities. We manage risk according to the Risk Management Framework and ensure all employees understand their individual accountability for managing risk.
The Risk Modeling Group (RMG) Team is a unit within the Corporate Credit Group, and is responsible for model development and implementation of the following model types:
Credit loss estimation models for the entire loan portfolio to support Allowance for Credit Loss (ACL), including preparations for Current Expected Credit Loss (CECL); estimation of risk weighted assets (RWA) in compliance with Basel regulations; and, economically sensitive credit loss estimation in compliance with Dodd Frank and the Comprehensive Capital Analysis and Review exercises (CCAR).
Models to support Pre-Provision Net Revenue (PPNR) estimates including forecasting models to support Dodd Frank and the Comprehensive Capital Analysis and Review exercises (CCAR).
Models to support Credit Decision, Fair lending and Operations Risk.
The Commercial Modeling team is seeking a dynamic leader with experience in predictive modeling and analytics to lead the model implementation and monitoring process development strategy for credit loss and balance forecasting models across all commercial and debt securities portfolios. These model implementation efforts will include integrated forecasting framework for stress testing, loss and balance forecasting, CECL/IFRS9, RRP (Recovery & Resolution Planning) and other in-model components/challenge credit/balance models used in various capacities.
This position will be part of the Commercial Modeling team and will report to the head of the Commercial and Basel Modeling leader. The individual will primarily focus on the designing integrated model implementation and forecasting processes while ensuring consistent practices across various model uses and applications while maintaining process quality and fast execution. The individual will engage with model development team, independent model production team, and business users to develop an effective model forecasting processes to meet model users' needs. He will organize and manage a team of model implementation and engineering talent; attracting talent; developing and conforming to Partnership Agreements (PAs) and meeting the needs of line of business credit and finance model owners.
This position joins a high functioning, high profile team, and requires the presence and professional demeanor necessary to interact effectively with team members across RMG, Lines of Business (LOB), credit officers, finance, model governance, oversight, validation, and audit organizations. The individual should have prior strong Python or similar programming language/tools experience and documentation capabilities that can effectively convey complex models and implementation processes.
The candidate must demonstrate strong data analysis skills, ability to understand underlying data and complex loss/balance forecasting models, various product features, possess organizational and prioritization skills, as well as strong attention to detail. This role is highly dynamic and will require critical thinking using both analytical and tactical approach to problem solving while managing and mentoring a team of analysts within the Commercial Model Implementation team.
The responsibilities of this position will include, but not be limited to, the following:
Develop and manage models implementation processes and strategy for credit loss, balance, spread/income forecasting and RRP valuation models for commercial loans and debt securities portfolio.
Leading a model implementation and engineering team to implement advanced statistical models in Python based modeling platform; Leading and developing team members including offshore resources.
Adhere to model validation, audit and governance requirements to ensure models implementation are in compliance with policy and are working as intended, timely address various stakeholders' feedback and issues.
Maintaining documentation for key processes and model components across the team with focus on standardization of processes; Engage model development teams, model production, and forecasting/model production team/users to develop consistent model implementation and process capabilities.
Participate in regular interactions with various stakeholders to enhance model implementation processes and translate requirements into integrated forecasting process/tools for effective consumption.
Understanding the trends within commercial loans portfolio, their impact on model implementation design and performance, and develop timely approach to address changes; Developing necessary analytics and processes during model implementation and forecasting process to provide production support and resolution.
Establishing consistent and robust model implementation processes across models with effective review and controls.
Staying abreast of the latest industry practices and tools with a focus to develop best practices and design; Develop a strong team which can quickly undertake and support model production activities as needed.
Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment to develop solutions while balancing multiple priorities.
Communicate design and results of models implementation to a variety of audiences, including senior management, bank supervisors, internal validation, Internal Audit and line of business credit and finance end users.
Coordinate with development teams including production teams, and end users to ensure accurate model usage and implementation.
4+ years of experience in an advanced scientific or mathematical field
2+ years of leadership experience
A master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science
Leadership experience with ability to effectively manage and engage teams
Excellent verbal, written, and interpersonal communication skills
Ability to identify and manage complex issues and negotiate solutions within a geographically dispersed organization
A PhD in a quantitative discipline
Strong organizational, multi-tasking, and prioritizing skills
Other Desired Qualifications
Experience with risk management of commercial loans and debt securities portfolios, product, and underwriting practices
Proven and demonstrated leadership skills in a model implementation or similar analytical settings
Ability to identify and manage complex issues and negotiate solutions within a geographically dispersed organization and business partners
Strong programming, large scale data querying (SQL) and analytics skills
Python, Spark, GitHub experience with prior experience in Advanced SAS, R
Experience implementing, coding, and de-bugging large and complex models
Sound background and understanding of modeling techniques like generalized linear models, hazard models, time series models (e.g. ARDL/ECM), panel regression models, and machine/statistical learning models (e.g. LASSO, Ridge Regression, Cross Validation)
Ability to articulate the strengths and weaknesses of various predictive modeling techniques
Strong understanding of statistical testing necessary to assess model performance
Experience in modeling concepts for CCAR, CECL/IFRS or Balance/Cash flow Forecasting applications
Experience with model risk management policies and procedures including regulatory guidance such as BCC 13-5, SR 11-7
Experience in working with large scale internal or external industry data as well as familiarity with regulatory reporting data sets (e.g. Call Reports, Y9C)
Proven track record of providing analytics for Credit organization within a large Financial Institution; including relationship-building and collaboration skills with clear ability to influence, gain buy-in and negotiate with a diverse group of key business partners/stakeholders including senior management
Intellectually curious, self-motivated with strong interests in developing new methods, processes and approaches
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.
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