Model Validation Director

Job Description

As a Director in the Quantitative Modeling job family you will apply extensive knowledge of advanced modeling techniques joining a modeling community which creates solutions that use public and proprietary data in all areas of the mortgage finance business including mortgage products and securities borrower behavior investment and hedging strategies residential property valuation macroeconomic models including of housing prices and interest rates valuation of financial assets and derivatives economic capital and stress testing.

As the Director in the Enterprise Model Risk group you will lead a team which conducts Risk Assessments and Model Validations of models which are used to support Operational decisions or Financial Forecasting Valuation and Risk Measurement.

THE IMPACT YOU WILL MAKE
The Model Validation Director role will offer you the flexibility to make each day your own while working alongside people who care so that you can deliver on the following responsibilities:

• Produce Validation Reports with the assistance of team members whose work you supervise including through defining the scope and plan for executing Validation Report production.
• Produce initial and ongoing Assessments of models evaluating performance-in-use and whether changes in the environment are creating increased model risk which needs to be mitigated.

Qualifications

THE EXPERIENCE YOU BRING TO THE TEAM

Minimum Required Experience

• 8 years of relevant experience in developing using or validating models

Desired Experience

• An advanced degree (PhD. or Masters) in a quantitative field such as Computer Science Statistics Biostatistics Economics (with an Econometrics emphasis) Applied Finance or Applied Mathematics
• Experience with the types of models used for supporting Operational areas including Technology Operations Information Security/Cyber Security and business processes which use AI/ML techniques in Image and/or Language Processing
• Experience with a large financial institution which has Enterprise Risk Management functions that meet the needs of highly regulated financial institutions

Skills

• Proficiency in the mathematical statistical and computer science techniques used in model development
• Ability to understand business contexts which create a need for models to support Operations often embedded within software applications used in business processes
• Fast-learning building on a strong foundation of knowledge to continuously learn new techniques for building and managing model risks well
• Communicating technical subject matter clearly and concisely both verbally and through well-written communications including Assessment Reviews and Validation Reports

Tools

Use programming languages most often used in model development such as Python and R