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The Counterparty Credit Risk Senior Architect position is a senior role that will interface closely with developers, quants and front office technology teams to improve the system architecture, the codebase organization, testing and release processes. The Analytical Calculation Engine (ACE) Development Team is responsible for developing and implementing the analytical models for derivatives credit risk and exposure calculations Firm-wide. This role will involve exposure to a wide range of technological frameworks, including high performance distributed computing and cloud.
Job Responsibility:
Developing and improving the Counterparty Credit Risk applications architecture
Optimize performance and consolidate the workflow across asset classes
Improving the CI/CD of the credit risk application
Extend and enhance existing test suites
Identifying and developing calculation optimization improvements
Serving as advisor or coach to new or lower-level developers
Exercising independence of judgement and autonomy
Acting as SME to senior stakeholders and/or other team members
Requirements:
Proven experience in software development or engineering roles
Excellent command of Python
Deep understanding of software design, architecture principles and industry best practices
Experience with distributed systems
Experience with CI/CD pipelines and Dev Ops practices
Ability to write clean, tested highly efficient code
Outstanding analytical and problem-solving skills
Solid mathematical finance and statistical analysis skills
Excellent verbal and written English
Strong leadership skills and experience working collaboratively within development teams
Ability to take ownership and proactively follow up on issues
Nice to have:
Good knowledge in C++
Knowledge of Rates, Credit, Equities, Commodities, FX derivatives and derivatives risk
Experience working on regulatory based projects such as Model Risk, Basel, Stress Testing, FRTB, SA CCR, CCAR
Experience with high performance and cloud computing
Familiarity with Numerical analysis/Monte-Carlo methods
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