Quantitative Analytics Cons 1

Job Description

The Corporate Credit & Market Risk group is responsible for independently overseeing the management of credit risk exposures (including monitoring and reporting on aggregate credit exposures across groups, legal entities, geographies, and jurisdictions) and the quality of credit risk management practices across the company. This oversight extends to all phases of a loan’s life cycle, including origination, underwriting, risk analysis, approval, documentation, boarding, monitoring, loss recognition, modification, and collection activities. Corporate Credit & Market Risk is responsible for delegating and/or removing credit and investment approval authorities to the lines of business.

More specifically, Corporate Credit & Market Risk develops, maintains and ensures adherence to enterprise-wide credit risk frameworks, policies, and procedures that are aligned with Board-approved risk appetite.

The Credit and PPNR Modeling (CaPM) organization is a unit within Corporate Credit and Market Risk and is responsible for model development and implementation of the following model types:

  1. 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).
  2. 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).

The Model Implementation and Production (MIP) team within CaPM Center of Excellence focuses on deploying Credit and PPNR models for production, including model implementation, production, and performance monitoring.

The team is seeking individuals with experience in predictive modeling and data analysis to join the Commercial and PPNR Loss Forecasting Production group within MIP. This role will focus on leading the implementation and execution of Credit models for Commercial portfolios and PPNR models in support of the Corporate and Regulatory (CCAR/DFAST) Stress Tests, ACL/CECL/IFRS9 processes, and financial business planning.

This position reports to Commercial Model Production Lead within the CaPM Model Implementation and Production team and will work closely with business partners to support model implementation, execution, performance monitoring, and reporting of Commercial credit models.

This position joins a high functioning, high profile, team and requires the presence and professional demeanor necessary to interact effectively with team members across CaPM, Lines of Business (LOB), model governance, oversight, validation, and audit organizations, as well as strong SAS/SQL programming skills and documentation capabilities that can effectively convey complex processes. The candidate must demonstrate strong SAS programming and data analysis skills, ability to understand complex credit loss forecasting and PPNR models, possess organizational and prioritization skills, as well as strong attention to detail. This role is highly dynamic and will require critical thinking and a tactical approach to problem solving.

The responsibilities of this position will include, but not be limited to, the following:

  • Leading development of complex stress test, ACL/CECL/IFRS9, and/or PPNR model implementation environments working with large data sets, advanced statistical models, and SAS coding to effectively and efficiently execute models for purposes including Annual Stress Tests/CCAR, ACL/CECL/IFRS9, and financial business planning
  • Establishing strong controls and creating consistent and robust execution processes across models
  • Establishing and cultivating relationships with the lines of business, model users, data, and model development teams
  • Coherently supporting analysis to a variety of audiences, including audit, regulatory agencies, management, and end users
  • Maintaining documentation for key implementation processes across the team with focus on standardization of implementation and execution controls
  • Leading and developing team members, including offshore resources

Wells Fargo & Company (NYSE: WFC) is a diversified, community-based financial services company. Founded in 1852 and headquartered in San Francisco, Wells Fargo provides banking, insurance, investments, mortgage, and consumer and commercial finance through our many locations, ATMs, the internet (wellsfargo.com) and mobile banking.

Required Qualifications

  • 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

Desired Qualifications

  • SAS experience
  • Excellent verbal, written, and interpersonal communication skills
  • Ability to articulate issues, risks, and proposed solutions to various levels of staff and management
  • Ability to identify and manage complex issues and negotiate solutions within a geographically dispersed organization
  • A PhD in a quantitative discipline

Other Desired Qualifications
  • Strong organizational and team management skills
  • Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities
  • A deep understanding of data and analytics across multiple product classes, systems, and organizations
  • Ability to drive decision making through a consensus building approach
  • Experience with risk management of commercial portfolios, products, and underwriting practices
  • Experience creating documentation of code used for audit or training of other programmers
  • Proficiency in model development and/ or implementation of large and complex predictive models for forecasting credit or PPNR losses using SAS, SQL, or other programming environment
  • Knowledge of SR15-18, BCBS 239 and other regulatory requirements on data and model usage/applications
  • Experience with Python and/or R

    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.

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