Quantitative Risk Model Developer

March 7, 2026

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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 arenaflex 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. Apply tot his job

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