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Quantitative Analytics Specialist 3 - Credit Risk Modeling
Company: Wells Fargo
Location: Des Moines, IA
Employment Type: Full Time
Date Posted: 04/17/2021
Expire Date: 05/23/2021
Job Categories: Banking, Finance/Economics, Financial Services, Information Technology, Insurance, Military, Quality Control, Research & Development
Job Description
Quantitative Analytics Specialist 3 - Credit Risk Modeling
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 and ensure all employees understand their individual accountability for managing risk

Corporate Risk helps all Wells Fargo businesses identify and manage risk. We help 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 Risk Modeling Team (the 'team') is a unit within Corporate Risk and is responsible for development and implementation of the following model types: 

  • Credit loss estimation models for loan portfolios to support allowance for credit loss, stress testing, and Basel.
  • 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.

The team is seeking a dynamic individual with experience in predictive modeling and data analysis to focus on developing, documenting and supporting models and results for Basel purpose. The selected candidate should possess credit risk modeling experience, strong Python and SAS/SQL programming skills as well as other quantitative skills. Our ideal candidate will have a sound background in modeling techniques like OLS and generalized linear models including logistic regression, hazard models, time-series and panel regression.  The same candidate is expected to bridge between parametric approaches and machine learning techniques. The selected candidate will be comfortable extracting data across a variety of data sources and databases.

Responsibilities

  • Responsible for model design, development, testing and documentation of PD (Probability of default ), Loss Given Default (LGD) and Exposure at Default (EAD) as well as Credit Risk Grades under Basel III framework
  • Coherently articulate analysis results to a variety of audiences and effectively collaborate with all stakeholders
  • Timely address model findings and respond to analytical requests from auditors and reviewers
  • Conduct data research and enhancement to facilitate modeling and analysis
  • 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
  • 5+ years of SQL or SAS experience



Desired Qualifications

  • A PhD in a quantitative discipline



Other Desired Qualifications
  • Five years of credit risk modeling/analytical experience in financial services industry
  • Demonstrated experience developing Basel PD/LGD/EAD models with advanced statistical methods
  • Strong analytical and problem-solving skills
  • Strong SAS/SQL and Python programming skills with experience in working with large datasets
  • Comprehensive understanding of statistical theories and applications
  • Familiar with modeling best practices in credit risk and banking industry
  • Knowledge of model life-cycle management
  • Expertise in Python and experienced in managing large files in a shared environment
  • Experienced in supervised and unsupervised machine learning methodology
  • Understanding of banking regulation and industry trends
  • Strong verbal, written, and interpersonal communication skills
  • Detail oriented, results driven, and able to navigate in a quickly changing and highly demanding environment where there are multiple dependencies


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.

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