Validating financial models

We are looking for someone like you to: • validate Treasury Risk models that are used exclusively in the US, and also perform detailed analysis and quality assurance on models validated at UBS Group or at offshore locations, to ensure alignment with SR 11-7, SR 15-18 and other US regulatory requirements.

• interface with US regulators, audit and model sponsors and US senior management on Treasury risk models (interest rates, liquidity), and therefore must be fully familiar with all the models in use and the corresponding regulations in the US.

The four phases include: soliciting applications from credit score model providers; reviewing submitted applications; conducting a credit score assessment; and assessing the model in conjunction with the GSEs’ business systems.

I am a native of Kansas City and have been fortunate to work with many of our largest companies Including the Federal Reserve Bank, Cerner, DST Output, and now UMB.

• strong quantitative developing and modeling skills in at least two of the following languages: C , R, SAS and Python.

• strong communication and presentation skills coupled with the ability to document validation reports effectively.

Join our webinar to learn about the challenges and benefits of incorporating machine learning models into your risk management program.

• act as the first point of contact in the US for all models, including those that are jointly used in the US and UBS Group, to communicate status of validation of these models to US legal entity governing bodies and bridge the time gap between US and the other locations (i.e.

London, Zurich and offshore locations.) • coordinate with Group counterparts and ensure that Group validators as well as offshore teams are fully engaged. Disclaimer / Policy Statements: UBS is an Equal Opportunity Employer.

The Great Recession taught us that the previous method for accounting for losses was “too little, too late”.

To ensure proper liquidity and capital ratios we must look to the future to determine the quality of our loan portfolios.

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