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We are looking to hire an experienced (VP level) quant modeler to join our Portfolio Risk Modeling team and lead core risk methodologies and full revaluation models. This individual would have a strong background in quantitative research, have demonstrable leadership skills as well as proven experience to work in a team environment, collaborating/guiding junior modelers and engineers. This person is expected to join as an individual contributor, leading key modeling initiatives, establishing proper governance and monitoring of these models.
Job Responsibility:
Lead core risk methodologies and full revaluation models
Leading key modeling initiatives, establishing proper governance and monitoring of these models
Primarily focused on full revaluation models, which span multiple fixed income and derivative products and lead to accurate risk assessment of these products
Work across asset class and drive synergy/innovation in conjunction with senior modelers in the global team
Requirements:
5–10 years of experience in market risk / derivative pricing / quantitative analytics within a financial services environment
Familiarity with instrument pricing models, and linear sensitivities-based approaches, scenario analysis, stress testing, and model behavior across market regimes
Solid foundation in mathematics and statistics (calculus, linear algebra, probability), with practical exposure to modeling or analytical problem-solving
Demonstrated exposure to model lifecycle and model governance, including performance monitoring and producing high quality technical documentation
Strong proficiency in Python for data-science workflows, hands on experience with numerical libraries (NumPy, pandas, SciPy), along-with experience with structured codebases
Proven track-record of working on cross-functional projects spanning quantitative, technology and validation teams
Experience owning or contributing to multi-month (6+ months) delivery initiatives, managing dependencies and milestones
Senior enough to engage confidently with peer-level and senior-stakeholders
Demonstrates end-to-end ownership mindset for a critical modeling estate
Applies structured thinking to decompose complex modeling and monitoring problems
Writes clean, readable, and well-structured code with appropriate abstractions
Comfortable balancing quantitative depth with engineering pragmatism
Capable of driving initiatives from concept to production in ambiguous and evolving problem spaces
Communicates with confidence and precision
Possesses a positive attitude and ability to work both independently and as part of a team
Ability to synthesize requirements from multiple stakeholders and translate those into actionable plans
Nice to have:
CFA / FRM / CQF is a plus
Advance degree in a quantitative discipline (Masters or Ph.D in Finance / Economics / Statistics / Financial Engineering or any equivalent quant discipline is preferred)