At Texas Capital Bank, we are driven by a single-minded and unwavering mission: to serve business and the individuals who run them. We use a consultative approach and innovative technologies to develop new ideas that give the bank and our clients a competitive advantage. We partner with our customers to push the boundaries of what’s possible—together.
Headquartered in Dallas, Texas Capital Bank has offices in Austin, Fort Worth, Houston, Richardson, Plano and San Antonio, and we serve clients in a variety of industries from coast-to-coast.
The successful candidate will be responsible in developing the bank’s next generation of credit loss models for the wholesale portfolio. The candidate will have quantitative background with modeling experience, and an ability to communicate and collaborate with different business units to effectively execute the tasks.
- Research, develop, and maintain quantitative/econometric models for assessing and forecasting credit risk.
- Prepare and analyze the loan data sets for statistical analysis to specify and estimate econometric models for purposes of CECL, stress testing, risk rating, and other credit risk related initiatives. Run regression (including time series and logistic regression) and other econometric analyses to develop credit risk models using statistical software such as R.
- Communicate model related information such as risk, performance and results to senior management and other business partners.
- Work closely with cross functional teams, including business stakeholders, model validation and governance teams, and model implementation team
- Work with Model Risk Management (MRM) to ensure models are compliant with MRM policy. Develop and maintain model documentation, procedures and performance monitoring framework in line with MRM policy.
- Proven track record for being able to work autonomously, work within a team environment, exhibiting demonstrated leadership and a strong desire to learn and contribute to a group.
- Advanced Degree (Masters required, PhD preferred) in Statistics, Applied Mathematics, Operations Research, Economics or other highly quantitative discipline
- Experience in statistical software packages such as R (preferred), Python and SAS.
- 5-10 years of hands on experience with the research, development, and implementation of credit risk models (estimating PD/LGD/EAD) for the commercial loan portfolio such as default models, transition models, loss-give-default models.