Quantitative Analytics Cons 2

Wells Fargo   •  

WV

Industry: Financial Services

  •  

5 - 7 years

Posted 365 days ago

5364314

Job Description

The Credit and PPNR Modeling (CaPM) Center of Excellence (CoE) resides within Corporate Credit and Market Risk and is responsible for development and implementation of the following models: 

  1. Credit loss estimation models for the entire loanportfolio 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 withDodd Frank and the Comprehensive Capital Analysis and Reporting 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 Reporting exercises (CCAR). 

The (CaPM) Modeling Team engages with team members throughout the bank to support the $800+B loanportfolio.  This includes partnering with the lines of business senior credit officers, CCAST, model governance, controllers and external reporting, and treasury. The team is also responsible for maintaining strong relationships with regulators, external auditors and other examiners.
The team is seeking a dynamic individual with experience in predictive modeling and data analysis to join the Commercial Modeling Team within the CaPM Group.  The Commercial Modeling Team is responsible for developing; documenting and supporting loss forecast models and results for Commercial Basel, Allowance and Stress Test Models. These models are leveraged for the bank's Allowance, Stress Testing and Loss forecasting processes.

This position requires application of analytical, statistical modeling, and forecasting methods and focuses on the theory and mathematics behind the analyses ofthese models, especially Allowance and Regulatory Capital Models.

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

  • Develop and manage model development strategy
  • Develop and document models to forecast conditional credit losses indicative of both Wells Fargo as well as industry level performance for commercial portfolio segments
  • Maintaining documentation for modeling processes with focus on state of the art and effective approaches used in the analysis and modeling processes
  • Work closely with line of business partners to enhance the theory behind existing loss models and forecast, address data and model questions.
  • Data Research and Analytics
  • Adhere to model validation governance to ensure models are in compliance with policy and are working as intended, address model validation and regulatory feedback issues
  • Coherently supporting analysis to a variety of audiences, including audit, regulatory agencies, management, and end users
  • Support ad hoc analytic projects

Required Qualifications

  • 4+ 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

  • A PhD in a quantitative discipline
  • An active Chartered Financial Analyst (CFA) designation
  • Excellent verbal, written, and interpersonal communication skills

Other Desired Qualifications

Our ideal candidate will have a sound understanding of credit risk modeling including a strong understanding of modeling techniques like generalized linear models, logistic regression, hazard models, time series models and Monte Carlo simulation.

Our ideal candidate will be able to articulate the strengths and weaknesses of various predictive modeling techniques and have a strong understanding ofstatistical testing necessary to assess model performance.

The following experience, knowledge, and skills are also highly preferred:

  • Strong programming, data querying and analysis skills
  • SAS programming and SQL experience
  • Experience driving credit portfolio modeling and strategy
  • Experience implementing and coding large and complex models
  • Knowledge of either Commercial or RetailBanking products
  • Detail oriented, results driven, and have the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities
  • Knowledge of SR15-18, BCBS 239 and other regulatory requirements on data and model usage/applications.
  • Prior experience or knowledge of risk management of commercial portfolios, product, and underwriting practices.