Risk Analytics Manager

Charles Schwab is a different kind of investment services firm – one that strives to disrupt the status quo of the traditional Wall Street approach on behalf of our clients. We believe today, as we did on Day 1, that when you find ways to improve the investing experience for your clients, then business results will follow.

We are looking for a Manager, Risk Analytics to drive model development and execution efforts related to retail credit loss forecasting. The incumbent will play a crucial role in developing quantitative analysis to support the ongoing credit risk model development efforts, and executing and refining the current loss forecasting process for first mortgages and HELOC. The candidate should have knowledge of lending products, and provide enhancements and support to existing models as well as developing new model initiatives.

* Perform statistical and econometric analyses of the mortgage portfolio * Leverage technology to implement process improvements * Assist in the development of additional credit loss forecasting models * Enhance model documentation, including additional backtesting, developmental evidence, and model limitations * Utilize project management and communication skills to ensure project deliverables are understood and achievable.

* Proficiency with quantitative and analytical methods and techniques * Ability to use technology to query databases and prepare documentation for senior management. * Ability to apply best practices related to the development of advanced quantitative models, including source code management, input variable stress analysis and overall model validation techniques. * Master’s degree in one of the following fields: finance, economics, financial engineering, applied and computational mathematics, and other disciplines in physical sciences or engineering that require heavy use of computational mathematics and/or statistical techniques * PhD preferred * 2-5 years of relevant statistical work experience within the Financial Services industry * Strong quantitative and coding skills * Proficiency in statistical packages such as R, Matlab, Python or Stata * Strong technical skills with experience using relational databases * Strong communication skills along with the ability to translate mathematical and statistical concepts to non-technical audiences, including senior management and auditors. * Knowledge of lending products (particularly first mortgage and HELOCs) and their performance drivers preferred