Quantitative Analytics Spec 3Job ID 5542168
Important Note: During the application process, ensure your contact information (email and phone number) is up to date and upload your current resume when submitting your application for consideration. To participate in some selection activities you will need to respond to an invitation. The invitation can be sent by both email and text message. In order to receive text message invitations, your profile must include a mobile phone number designated as “Personal Cell” or “Cellular” in the contact information of your application.
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. The team focuses on several key risk types, including conduct, credit, financial crimes, information security, interest rate, liquidity, market, model, operational, regulatory compliance, reputation, strategic, and technology risk.
The group provides leadership, enhances communications, assists with problem identification and solutions, and shares best practices. In addition, the group provides an enterprise-wide view of risk, assists management and our Board of Directors in identifying and monitoring risks that may affect multiple lines of business, and takes appropriate action when business activities exceed the risk tolerance of the company.
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:
- Credit loss estimation models for the entire loan portfolio to support estimation of allowance for credit loss (including current expected credit loss preparation); economically sensitive credit loss estimation in compliance with Dodd Frank and the Comprehensive Capital Analysis and Reporting exercises (CCAR); and risk weighted assets (RWA) in compliance with BASEL regulations.
- 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).
- We are seeking a dynamic individual with experience in predictive modeling and data analysis to join the Commercial Modeling Team that is responsible for developing, documenting, and supporting Commercial portfolio in the following areas:
- Credit Loss forecast models for Allowance, Stress Testing and Capital
- Balance/Interest Income forecast models
The bank leverages these models for the stress testing, reserve and capital setting processes for various commercial portfolios and segments. This position requires application of analytical, statistical modeling, and forecasting methods and focuses on the theory and mathematics behind the analyses.
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), 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 modeling and data analysis skills; ability to understand various product features, underlying data, and complex loss/balance forecasting models; as well as strong attention to detail. This role is highly dynamic and will require critical thinking and both analytical and tactical approach to problem solving.
Responsibilities of this role will include, but not be limited to the following:
- Develop and document models to forecast credit losses, balances/interest income for commercial portfolio segments
- Develop necessary data analytics and processes during model development process for enhancing model performance
- Provide analytical support and offer insights for analytic projects, data research, and modeling research
- Contribute to the improvement of model development, implementation, and use practices
- Work closely with line of business, credit and finance partners to enhance the theory behind existing models and forecast, address data and model questions
- Coordinate with production teams 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
- Coherently support analysis and effectively communicate with business partners, model validation, audit, and regulators as required
Available Locations: Minneapolis, MN and Charlotte, NC
Other Desired Qualifications
- A PhD in a quantitative discipline such as mathematics, statistics, engineering, physics, quantitative finance, economics or computer sciences, with strong quantitative and analytical skills
- Strong programming, large scale data querying (SQL) and analysis skills
- Advanced SAS, Python and R programming experience
- Experience implementing, coding and de-bugging large and complex models
- Strong programming, large scale data querying (SQL) and analysis skills
- Knowledge of either Commercial or Retail Banking credit products, and underlying portfolio measures
- Direct experience in model development for loss forecasting, balance/interest income forecasting considering factors such as amortization, attrition, and yields
- Experience working with variety of internal or external data sources and develop forecasting applications Familiar with ALM/Treasury concepts such as EVE, Funds Transfer Pricing, Net Interest Income Simulation
- Conceptual understanding of interest rate and yields curve models
- Familiar with regulatory reporting data sets (e.g. Call Reports, Y9C, 14a); applications such as QRM, SNL
- Experience in writing strong model documentation and creating analytical presentations
- Intellectually curious, self-motivated with strong interests in developing new methods, processes and approaches
- Detail oriented, results driven, and able to balance priorities in dynamic environment
- Sound understanding of credit, balance/interest income modeling techniques
- In-depth understanding of linear models, logistic regression, hazard models, time series models, panel regression models, and machine/statistical learning models (e.g. LASSO, Ridge, Cross Validation)
- Ability to articulate the strengths and weaknesses of various predictive modeling techniques
- Strong understanding of statistical testing necessary to assess model performance
NC-Charlotte: 11625 N Community House Road - Charlotte, NC
MN-Minneapolis: 600 S 4th St - Minneapolis, MN
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.