PPNR Model Development Manager - QAM 1

Wells Fargo   •  


Industry: Financial Services


5 - 7 years

Posted 362 days ago


Job Description

The Credit and PPNR Modeling (CaPM) Team is a unit within the Corporate Credit and Market Risk Group, 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 incompliance 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 team is seeking a dynamic Quantitative Analytics Manager with experience in predictive modeling and data analysis to lead the development strategy for deposit balance forecasting models. This position will be part of the PPNR modeling organization and will be responsible for driving the development ofbalance forecasting models; organizing and managing a team of model development talent; attracting talent; developing and conforming to Partnership Agreements (PAs) and meeting the needs of line of business 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 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 models and processes. The candidate must demonstrate strong SAS programming and data analysis skills, ability to understand complex loss forecasting and PPNR models, possess organizational and prioritization skills, as well as strong attention todetail. This role is highly dynamic and will require critical thinking and both analytical and tactical approach to problem solving.

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

  • Develop and manage model development strategy for balance forecasting of deposits.
  • Communicate design and results of complex models to a variety of audiences, including senior management, bank supervisors, CMoR, Internal Audit and LOB end users. Coordinate with business partners, including production teams, and end users to ensure accurate model usage and implementation
  • 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.
  • Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities

Required Qualifications

  • 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

Desired Qualifications

  • 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
  • Leadership experience with ability to effectively manage and engage teams

Other Desired Qualifications

  • Proven and demonstrated leadership skills in a model development or analytical setting
  • Ability to identify and manage complex issues and negotiate solutions within a geographically dispersed organization
  • Proven track record of providing analytics for Finance/Treasury organization within a large Financial Institution
  • Experience with model risk management policies and procedures
  • Experience working with federal regulatory agencies, in particular the OCC and FRB
  • 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, Cross Validation)
  • Experience with modeling deposit attrition, balances, and yields
  • Familiar with concepts/theory behind money creation and demand
  • Familiar with ALM/Treasury concepts such as EVE, Funds Transfer Pricing, and Net Interest Income Simulation
  • Conceptual understanding of methods to value products with implied optionality (e.g. Deposits, Mortgages)
  • Conceptual understanding of interest rate and yields curve models
  • Familiar with regulatory reporting data sets (e.g. Call Reports, Y9C)
  • SAS, SQL, and R experience