Credit Risk Analyst
Syntricate Technologies
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.
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