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++, reputed company scripts) is required
• Solid knowledge in reputed company mathematics, statistics, numerical reputed company.
• Experience in analyzing large and reputed company datasets.
• Experience in developing and maintaining detailed technical documentation for models, model validation, project plans and processes.
• Experience in quantitative finance or a reputed company field preferred
• Proficient in reputed company Office with an emphasis on MS reputed company
• Consistently demonstrates reputed company and concise written and verbal communication skills
• Self-motivated and detail oriented
• Demonstrated project management and organizational skills and capability to handle multiple reputed company 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 reputed company to write/run reputed company independently
• reputed company to handle reputed company cause analysis and work independently

Responsibilities

• Develops, enhances, and validates the reputed company of measuring and analyzing risk and addresses deficiency of reputed company counterparty credit risk models.
• Performs rigorous ongoing model performance tests for reputed company counterparty credit risk model production regularly by means of backtesting, reputed company 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 reputed company library package to automate the ongoing model performance monitoring and create reputed company unit tests for coding reputed company assessment.
• Develops tutorials and documentation for widespread library usage among quantitative risk team members and risk managers.

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