Quantitative Risk Model Developer

Quantitative Risk Model Developer Tampa, FL (3 days onsite - Hybrid) 12+ Months Web Cam Interview $70/Hr on W2 Must Haves: Master's Degree with 2 years of working experience or Bachelor's Degree with 4 years of working experience 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. Plusses: 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. General Notes: Solid programming background in Python Statistics and numerical experience, hypothetical testing, and should be able to write/run code independently Able to handle root cause analysis and work independently 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 backtesting, impact analysis, statistical analysis, etc. Enhances BAU backtesting 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.