Grow your career as a Quantitative Analyst Developer with an innovative global bank in Tampa, FL. Contract role with strong possibility of extension. Will require working a hybrid schedule 2-3 days onsite per week.

Join one of the world's most renowned global banks and trusted brand with over 200 years of continuously evolving financial services worldwide. You will work alongside some of the smartest minds in the industry who are excited to share their knowledge and to learn from you.

Contract Duration: 9+ Months

Required Skills & Experience

• Master's degree in quantitative field (e.g. quantitative finance, finance engineering, economics, computer science, statistics, mathematics, engineering, etc.).
• 2 years of experience.
• Proficiency in programming language (e.g. Python, R, C++, shell scripts).
• 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.
• Proficient in Microsoft Office with an emphasis on MS Excel.
• Demonstrated project management and organizational skills and capability to handle multiple projects at one time.

Desired Skills & Experience

• 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.
• Experience in quantitative finance or a related field.

What You Will Be Doing

• Develop, enhance, and validate the methods of measuring and analyzing risk and addresses deficiency of current counterparty credit risk models.
• Perform rigorous ongoing model performance tests for all counterparty credit risk model production regularly by means of backtesting, impact analysis, statistical analysis, etc.
• Enhance BAU backtesting to meet the regulatory guidelines.
• Prepare 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.
• Develop unified library package to automate the ongoing model performance monitoring and create related unit tests for coding quality assessment.
• Develop tutorials and documentation for widespread library usage among quantitative risk team members and risk managers.