Counterparty Risk Analytics - Quantitative Analyst
- Key responsibilities:
- The Counterparty Risk Analytics team is responsible for developing and maintaining the methodologies to calculate counterparty credit risk exposures of OTC derivatives (cleared and non-cleared), Exchanged-Traded derivatives, Security Financing Transactions, and Margined Loans. The models are used for advanced Basel regulatory capital calculations, CCAR/ICCAP estimates, and internal risk management measures (PSE/PSLE).
- Besides model use supports, the team also provides live-deal analysis to business and risk management by calculating credit exposure factors (CEF) at trade and portfolio levels, estimating allowable collateral levels, and determining initial margin requirements. They also conduct impact analysis for capital optimization initiatives and new regulatory rules related to counterparty risk. They support to ensure that models and data logics are implemented correctly in credit risk systems.
Key responsibilities include:
- Enhance Linux/C++ based counterparty credit exposure simulation and pricing models for OTC derivatives, covering all major asset types (EQ, IR/FX, Credit, Commodity)
- Perform rigorous model testing for all production models, including backtesting, stress testing, and other testing involved in the model development process
- Analyze and provide comprehensive explanation of testing results to model reviewers including model validation, risk managers, and senior management
- Perform statistical analysis on large volume of financial data, such as historical data analysis and simulation model parameter calibration
- 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
- Support and Enhance stress testing applications for derivatives and SFT. Support regulatory stress testing including CCAR and ICAAP.
- Minimum of a Master's degree in quantitative field (e.g. mathematics, physics, statistics, engineering, economics, finance, financial engineering, etc.) with 3+years of relevant experience.
- Fewer years of relevant experience will be considered for candidates with higher academic qualifications and/or certifications such as a PhD, a second Master's degree, CPA or CFA.
- Solid programming skills. Ideally from an object oriented language such as C++ and scripting language such as Python or Perl
- Basic knowledge of financial products and derivatives modeling
- Great communications skills in both verbal and written
Grade :All Job Level - All Job FunctionsAll Job Level - All Job Functions - US
Time Type :Full time
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