Credit Risk Analyst Tampa, FL (Hybrid) 10+ Months Web Cam Interview $70/Hr on W2 Responsibilities • Develops, enhances, and validates the methods of measuring and analyzing risk and addresses deficiency of current counterparty credit risk models.
- Performs rigorous ongoing model performance tests for all counterparty credit risk model production regularly by means of back testing, impact analysis, statistical analysis, etc.
- Enhances BAU back testing to meet the regulatory guidelines.
- Prepares detailed technical documentation report for validation purposes sufficient to meet regulatory guidelines and exceed industry standards.
- Present key findings in model development and enhancement to senior management and supervisory authorities.
- Support trading book credit risk management: calculate portfolio level counterparty exposure such as EPE, EAD, CVA, used for both internal risk management, regulatory capital calculation and stress testing.
- Develops unified library package to automate the ongoing model performance monitoring and create related unit tests for coding quality assessment.
- Develops tutorials and documentation for widespread library usage among quantitative risk team members and risk managers.
Qualifications: • Proficiency in programming language (e.g. Python, R, C++, shell scripts) is required
- Solid knowledge in applied mathematics, statistics, numerical methods.
- Experience in analyzing large and complex datasets.
- Experience in developing and maintaining detailed technical documentation for models, model validation, project plans and processes.
- Experience in quantitative finance or a related field preferred
- Proficient in Microsoft Office with an emphasis on MS Excel
- Consistently demonstrates clear and concise written and verbal communication skills
- Self-motivated and detail oriented
- Demonstrated project management and organizational skills and capability to handle multiple projects at one time.
Education: • Master's degree in quantitative field (e.g. quantitative finance, finance engineering, economics, computer science, statistics, mathematics, engineering, etc.) with 2 years of relevant experience OR Ph.D. degree in quantitative field (e.g. quantitative finance, finance engineering, economics, computer science, statistics, mathematics, engineering, etc.) with research experience in modeling and numerical simulation.