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.

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