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Wells Fargo Quantitative Analytics Spec 3 in Des Moines, Iowa

Job Description

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 are looking for talented people who will put our customers at the center of everything we do. We are seeking candidates who embrace diversity, equity and inclusion in a workplace where everyone feels valued and inspired.

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

As the company's second line of defense, Corporate Risk — or Independent Risk Management — provides independent oversight of risk-taking activities. Independent Risk Management establishes and maintains Wells Fargo's risk management program and provides oversight, including challenges to and independent assessment of, the frontline's execution of its risk management responsibilities. We manage risk according to the Risk Management Framework (https://portal.teamworks.wellsfargo.net/rc/CorporateRisk/Pages/riskmgmtfrmwk.aspx) and ensure all employees understand their individual accountability for managing risk.

The Risk Management Group (the “team”) is a unit within Corporate Credit and is responsible for model development and implementation of the following model types:

I. Pre-Provision Net Revenue (PPNR) estimates, including forecasting models, to support stress-testing under the Comprehensive Capital Analysis and Reporting exercises (CCAR) and nine-quarter business forecasting.

II. 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 stress-testing for the Comprehensive Capital Analysis and Reporting exercises (CCAR).

The team is seeking a dynamic individual with experience in predictive modeling and data analysis to join the model development team focusing on deposit forecasts for balances and rates. The team is responsible for developing, documenting and supporting models and results. The selected candidate will be able to articulate the strengths and weaknesses of various predictive modeling techniques and have a strong understanding of statistical testing necessary to assess model performance. The candidate must be able to bridge the gap between theory and practice to deliver projects suitable for the intended business purpose – stress testing and business forecasts of fee revenue and expense.

Our ideal candidate will have a sound background and understanding of PPNR modeling including a strong understanding of modeling techniques like OLS and generalized linear models including logistic regression, hazard models, time-series, and panel regression. The same candidate would be able to bridge between parametric approaches to analysis and machine learning techniques. She/he will appreciate the use of modeling approaches such as penalized regression, spline-fitting, or spectral analysis and how they relate to models built using piecewise regression or some other extension of the linear model tradition.

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

  • Developing deposit balance and rate-paid forecasting models

  • 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

  • Create long-form presentation documents to explain the model results to both technical and non-technical audiences

  • Develop and document models to forecast conditional results indicative of both Wells Fargo and industry level performance

  • Work closely with line of business partners to develop and enhance the theory and business logic behind the models and forecasts; address data and address questions from our partners, model validation, and regulators.

  • Data research to facilitate modeling and analysis

  • 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 articulate analysis results to business partners, model validation, audit and regulators

  • Support ad hoc analytic projects

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

  • A PhD in a quantitative discipline

  • Excellent verbal, written, and interpersonal communication skills

Other Desired Qualifications

  • SAS, SQL, and Python programming skills for data analysis

  • Knowledge of time-series regression and forecasting models

  • Experience implementing and coding large and complex models

  • Knowledge of bank products across consumer, wholesale, and trust and investment

  • Detail oriented, results driven, and has the ability to navigate in a quickly changing and highly demanding environment while balancing multiple priorities

  • Understanding of bank regulatory data sets and other industry data sources

  • Experience using Teradata

  • A willingness to take a lead role on projects, while functioning effectively as part of a team.

  • An understanding of the importance of, and the ability to manage to, deadlines in an environment where there are multiple dependencies on the outcome of one’s work is essential.

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.

Benefits Summary

Benefits

Visit https://www.wellsfargo.com/about/careers/benefits for benefits information.

Company: Wells Fargo

Req Number: 5589366-4

Updated: 2021-07-30 00:23:14.605 UTC

Location: Des Moines,IA

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