Risk Analytics Sr. Analyst

Texas Capital is built to help businesses and their leaders. Our depth of knowledge and expertise allows us to bring the best of the big firms at a scale that works for our clients, with highly experienced bankers who truly invest in people’s success — today and tomorrow.  

While we are rooted in core financial products, we are differentiated by our approach. Our bankers are seasoned financial experts who possess deep experience across a multitude of industries. Equally important, they bring commitment — investing the time and resources to understand our clients’ immediate needs, identify market opportunities and meet long-term objectives. At Texas Capital, we do more than build business success. We build long-lasting relationships. 

Texas Capital provides a variety of benefits to colleagues, including health insurance coverage, wellness program, fertility and family building aids, life and disability insurance, retirement savings plans with a generous 401K match, paid leave programs, paid holidays, and paid time off (PTO). 

Headquartered in Dallas with offices in Austin, Fort Worth, Houston, Richardson, Plano and San Antonio, Texas Capital was recently named Best Regional Bank in 2024 by Bankrate and was named to The Dallas Morning News’ Dallas-Fort Worth metroplex Top Workplaces 2023 and GoBankingRate’s 2023 list of Best Regional Banks. For more information about joining our team, please visit us at www.texascapitalbank.com. 

Brief Overview of Position

The Risk Analytics Sr. Analyst is accountable for leading the specialized credit risk analysis, risk rating systems, and introducing new data science techniques and methodologies to support risk management. The primary purpose of this job is development and implementation of financial risk management models, including financial valuation and Counterparty Credit Risk (CCR) exposure models using analytical methods, Monte Carlo simulation, and statistical techniques. This includes design, Python code development, testing and implementation of market risk stress-testing focused models, and performing any ad-hoc analysis to support overall portfolio and LOB analytics. This role requires work coordination with Corporate & Investment Banking, Finance, Accounting, Risk Management, Model Development, Data Management, and Audit.

Responsibilities

• Develop methodologies and tools to support Market and Liquidity Risk in measuring pre-trade counterparty risk exposure and day-to-day stress testing of bank's trading portfolio (EQ, FICC, Muni, Sec Prod, Rates).
• Provide analytics for Capital Stress Test, CECL business decisions, evaluate, and support the reasonability of estimation results, and assess and recommend key management assumptions for use in the ACL estimation process.
• Documentation, monitoring, and validation of the models.
• Provide data science and modeling expertise to the projects in designing credit risk strategies and solutions, with strategic implications.
• Partner with risk and lines of business teams to develop analytic solutions, ad-hoc analysis, and modeling to drive new initiatives, improve business processes and deliver value using data-driven decisions.
• Cross-functional relationships - coordinate with the accounting policy, controller, and finance functions.
• Communication with model validation, internal auditors, external auditors, and external regulators.

Qualifications

• Master’s Degree or higher in Math, Statistics, Finance, Computer Science, or another quantitative field.
• Minimum of 5 years of experience in quantitative analysis/modeling, credit policy, or credit risk management in the financial services industry.
• Proven record of strong work ethics with a commitment to transparency, accountability, and collaborative work.
• Understanding of risk modeling and data management, database concepts, and data structures.
• Understanding of credit risk management discipline, principles, and regulatory requirements – GAAP, CECL accounting standard, CCAR.
• Proficiency with Python and R and the associated analytics packages. Exposure to SQL, Microsoft Azure, Tableau, and Shiny is desirable.