Wells Fargo

Job Category:

Risk/Compliance

Location:

Charlotte, North Carolina

Country:

United States

Postal Code:

28201

Approximate Salary:

Not Specified

Position Type:

Full Time

Phone:

415) 820-7800

Credit Risk Analytics Consultant 4

Wells Fargo - Charlotte, North Carolina

Posted: 10/2/2018

Job Description

At Wells Fargo, we want to satisfy our customers’ financial needs and help them succeed financially. We’re looking for talented people who will put our customers at the center of everything we do. Join our diverse and inclusive team where you’ll feel valued and inspired to contribute your unique skills and experience.

Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.

Corporate Risk helps all Wells Fargo businesses identify and manage risk. We focus on three key risk areas: credit risk, operational risk and market risk. We help our management and Board of Directors identify and monitor risks that may affect multiple lines of business, and take appropriate action when business activities exceed the risk tolerance of the company.

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

I. Credit loss estimation models for the entire loan portfolio to support allowance for credit loss (including current expected credit loss preparation); 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).
II. Models to support Pre-Provision Net Revenue (PPNR) estimates including forecasting models to support Dodd Frank and the Comprehensive Capital Analysis and Reporting exercises (CCAR).

This position will focus on supporting the production of credit models in support of the Corporate and Regulatory Stress Tests and Allowance for Credit Loss (ACL) / Business Loss Forecast (BLF) processes for the consumer unsecured credit portfolios, including Consumer Financial Services (credit cards), Retail Services (retail cards), and Personal Lending Group (student loans and personal loans and lines). This candidate will also develop and implement analytical reporting to help explain incremental loss contributions by different risk drivers for ACL, BLF, and CCAR. This position joins a high functioning, high profile team and requires strong SAS/SQL programming skills, documentation capabilities that can effectively convey complex processes, and the presence and professional demeanor necessary to interact effectively with team members across the Company. The candidate must demonstrate strong SAS programming and data analysis skills, ability to understand complex loss forecasting 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 and production design. The candidate must have demonstrated experience in working with modelers, implementation owners, and model risk governance to develop efficient model production engines in a process controlled environment. The candidate will also help design, enhance, and implement a comprehensive model monitoring and production process for ACL, BLF, and CCAR. Given the nature of the model implementation and production schedule, this role is expected to sometimes work nights or weekends and needs to be reached during the ACL / BLF production and CCAR / MCST time.

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

• Lead the development of complex stress test and ACL/BLF production environments working with large data sets, advanced statistical models, and SAS/other coding to effectively and efficiently execute models for purposes including Stress Tests/CCAR, ACL/BLF, and model performance monitoring
• Serve as a liaison with business partners, including data teams, implementation teams, and end users to ensure accurate model implementation, provide support on model execution, and create consistent processes for reporting results
• Develop and support strong controls for the model implementation framework and maintain related documentation
• Coherently support analysis for business partners, audit, and regulatory agencies

Required Qualifications

  • 7+ years of risk reporting experience, risk analytics experience, or a combination of both
  • 3+ years of leadership experience
Desired Qualifications

  • Excellent verbal, written, and interpersonal communication skills
  • Outstanding problem solving skills
  • SAS programming experience in model implementation, reporting, and complex data manipulations
  • Strong analytical skills with high attention to detail and accuracy
Other Desired Qualifications
  • Advanced degree in quantitative field is preferred
  • Good understanding of model concept / framework, model monitoring and analytical reporting
  • Experience transforming data and pulling code (from modelers) to an easy-to-understand format, including structuring the output data in a manner that it can be used for multiple downstream processes (i.e. forecast / back test results, KPI monitoring, etc.)
  • Experience applying credit risk management principles
Street Address

NC-Charlotte: 11625 N Community House Road - Charlotte, NC
IA-Des Moines: 800 Walnut St - Des Moines, IA
MN-Minneapolis: 600 S 4th St - Minneapolis, MN

Disclaimer

  • 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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