Citi
Quantitative Analyst - Counterparty Credit Risk Development, VP
Citi, New York, New York, us, 10261
Overview
The Counterparty Credit Risk Quant Development Team, a key group within Markets Quantitative Analysis Organization, is responsible for developing cutting-edge analytical models for derivatives risk and exposure calculations Firm-wide. The scope of this role extends from the research into the mathematical derivation of advanced quantitative models, through coding, testing, documentation for formal validation and approval, and delivering these models for integration into the Firm's internal and regulatory risk management processes. Responsibilities
Leading the development and maintenance of in-house C++ and Python model libraries. Pioneering advancements in the quantitative toolbox through the development of new technologies, algorithms, and numerical techniques. Driving efficiency improvements and optimization within the analytical libraries. Collaborating with IT teams to integrate complex analytic libraries into production systems. Overseeing the development and maintenance of critical quant infrastructure, databases, and productivity tools. Providing expert support for the build, rigorous testing, and release management of the model libraries. Engaging in Regulatory and Governance-based projects, particularly those related to Counterparty Credit Risk (CCR) such as Basel IMM, PFE, CVA, and RWA calculations, across asset classes. Performing in-depth data analysis and producing comprehensive regular reports. Required Skills
Demonstrable expertise and a proven track record in developing and supporting analytics libraries for the pricing, risk, and exposure calculation of complex financial derivatives. Strong preference for experience in Equity derivatives pricing, including stochastic volatility models, variance swaps, correlation products, and exotic structures. Deep familiarity with Counterparty Credit Risk (CCR) calculations, including Basel IMM, Potential Future Exposure (PFE), EPE, EAD, and CVA methodologies. Experience on other Regulatory-based projects such as Model Risk, Basel III, Stress Testing, FRTB, and CCAR is advantageous. Solid mathematical finance and advanced statistical analysis skills. Proficiency in probability theory and stochastic calculus. Extensive familiarity with Numerical Analysis and Monte-Carlo methods. Proven experience developing robust software for Windows and Linux environments. Excellent command of scripting using UNIX Shell (ksh, bash, etc.), Python, and VBA. Knowledge of Relational Databases (e.g., Mongo) is a plus. Knowledge/experience with Machine Learning Tools and Frameworks (e.g., scikit-learn, PyTorch) is a plus. Exceptional command of programming using modern C++ and Python. Outstanding analytical and complex problem-solving skills. A meticulous and detail-oriented approach with a commitment to accuracy. Ability to strictly follow procedures and operate within stringent guidelines. Excellent verbal and written English communication skills. Strong ownership mentality and proactive issue follow-up. Ability to work effectively in a team and perform well under pressure. Education
Bachelor’s/University degree; Master’s degree preferred Note: This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. Anticipated Posting Close Date
Nov 02, 2025 Citi is an equal opportunity employer. Qualified candidates will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, this describes accessibility options and the Citi Know Your Rights posters. For additional information regarding Citi employee benefits, please visit citibenefits.com.
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The Counterparty Credit Risk Quant Development Team, a key group within Markets Quantitative Analysis Organization, is responsible for developing cutting-edge analytical models for derivatives risk and exposure calculations Firm-wide. The scope of this role extends from the research into the mathematical derivation of advanced quantitative models, through coding, testing, documentation for formal validation and approval, and delivering these models for integration into the Firm's internal and regulatory risk management processes. Responsibilities
Leading the development and maintenance of in-house C++ and Python model libraries. Pioneering advancements in the quantitative toolbox through the development of new technologies, algorithms, and numerical techniques. Driving efficiency improvements and optimization within the analytical libraries. Collaborating with IT teams to integrate complex analytic libraries into production systems. Overseeing the development and maintenance of critical quant infrastructure, databases, and productivity tools. Providing expert support for the build, rigorous testing, and release management of the model libraries. Engaging in Regulatory and Governance-based projects, particularly those related to Counterparty Credit Risk (CCR) such as Basel IMM, PFE, CVA, and RWA calculations, across asset classes. Performing in-depth data analysis and producing comprehensive regular reports. Required Skills
Demonstrable expertise and a proven track record in developing and supporting analytics libraries for the pricing, risk, and exposure calculation of complex financial derivatives. Strong preference for experience in Equity derivatives pricing, including stochastic volatility models, variance swaps, correlation products, and exotic structures. Deep familiarity with Counterparty Credit Risk (CCR) calculations, including Basel IMM, Potential Future Exposure (PFE), EPE, EAD, and CVA methodologies. Experience on other Regulatory-based projects such as Model Risk, Basel III, Stress Testing, FRTB, and CCAR is advantageous. Solid mathematical finance and advanced statistical analysis skills. Proficiency in probability theory and stochastic calculus. Extensive familiarity with Numerical Analysis and Monte-Carlo methods. Proven experience developing robust software for Windows and Linux environments. Excellent command of scripting using UNIX Shell (ksh, bash, etc.), Python, and VBA. Knowledge of Relational Databases (e.g., Mongo) is a plus. Knowledge/experience with Machine Learning Tools and Frameworks (e.g., scikit-learn, PyTorch) is a plus. Exceptional command of programming using modern C++ and Python. Outstanding analytical and complex problem-solving skills. A meticulous and detail-oriented approach with a commitment to accuracy. Ability to strictly follow procedures and operate within stringent guidelines. Excellent verbal and written English communication skills. Strong ownership mentality and proactive issue follow-up. Ability to work effectively in a team and perform well under pressure. Education
Bachelor’s/University degree; Master’s degree preferred Note: This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. Anticipated Posting Close Date
Nov 02, 2025 Citi is an equal opportunity employer. Qualified candidates will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, this describes accessibility options and the Citi Know Your Rights posters. For additional information regarding Citi employee benefits, please visit citibenefits.com.
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