VP Quantitative Strategist - ALM & IRRBB

Goldman Sachs; Dallas, Northern (TX, KY); Hybride; USD 180 000 - 260 000; Plein temps

Avantages offerts par ce poste

Health insurance

Retirement benefits

Wellness programs

Employee assistance programs

Résumé du poste

Goldman Sachs in Dallas seeks a Vice President in Core Engineering, Quantitative Engineering to lead ALM risk quantification and IRRBB modelling. You will design and maintain quantitative models, build robust analytics, and communicate results to cross-functional teams.

The role requires 5+ years in finance, an advanced quantitative degree, and strong programming in C++, Java, or Python. Collaboration with global Strats and a fast-paced environment are core features.

Qualifications

• 5+ years of experience in the financial industry, preferably within Capital Markets, Risk, or Treasury functions.
• Advanced academic background in a highly quantitative field; MS or PhD strongly preferred.
• Strong programming skills in C++, Java, or Python.
• Exceptional quantitative analysis with modeling and data handling experience.
• Strong written and verbal communication to explain complex concepts.

Responsabilités

• Design, implement, and maintain quantitative models and IRRBB risk frameworks.
• Build analytics for interest rate sensitivity and scenario analysis across portfolios.
• Enhance methodologies for interest rate risk metrics with stakeholders.
• Maintain model lifecycle documentation and support regulatory inquiries.
• Deliver clear presentations of model outputs to managers and teams.
• Collaborate with the global Strats team to drive high-impact deliverables.

Connaissances

C++

Java

Python

Analytical skills

Communication

Formation

Master's degree or PhD in Mathematics/Physics/Statistics/Engineering/CS

Description du poste

Goldman Sachs in Dallas seeks a Vice President in Core Engineering, Quantitative Engineering to lead ALM risk quantification and IRRBB modelling. You will design and maintain quantitative models, build robust analytics, and communicate results to cross-functional teams.

The role requires 5+ years in finance, an advanced quantitative degree, and strong programming in C++, Java, or Python. Collaboration with global Strats and a fast-paced environment are core features.