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Tier-1 brand and metro location increase applicant density but niche C++ quant skillset limits competition.
High—requires specialized quantitative finance, exposure/XVA and risk platform experience, reducing cross-industry transferability.
High—mandatory expert Python and C++ plus specialized derivatives/risk analytics platform experience are required.
Design, develop, and maintain Citi's derivatives credit risk analytics platform (ACE), focusing on high-performance, scalable risk calculations.
Collaborate with Quantitative Research and Front Office teams to integrate pricing models and enhance computational efficiency.
Lead application modernization efforts and deliver key business and regulatory risk analytics capabilities across multiple asset classes.
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Financial Engineering, or related quantitative discipline required.
Expert-level Python and strong C++ programming experience with production-grade analytics libraries.
Experience in Capital Markets, Risk Technology, Quantitative Analytics, or Financial Services environments.
Work Experience Required: Not explicitly mentioned in the JD.
Demonstrates strong software engineering skills combined with understanding of quantitative finance and risk management.
Experienced in developing large-scale, high-performance risk analytics solutions for derivatives and credit risk.
Ability to collaborate closely with quantitative researchers, model developers, and technology teams to deliver complex risk calculation workflows.