Quant Modeling Lead, Model Risk Governance Review, Vice President

What you'll do

• Assess Asset Management models against robust development and testing standards to enhance validation practices.
• Evaluate model design soundness, input reliability, implementation correctness, and the suitability of performance metrics.
• Identify weaknesses and emerging risks through hands-on independent testing and the development of benchmark models.
• Document high-quality validation reports and communicate material findings and business implications to senior stakeholders.
• Support model-related audits and regulatory examinations by providing clear analysis and supporting documentation.
• Incorporate industry best practices and regulatory developments into independent assessments and validation methodologies.
• Manage review deliverables independently while collaborating with developers and users to resolve findings.

What we're looking for

• A PhD or Master’s degree in a quantitative field such as Mathematics, Physics, Engineering, Computer Science, Economics, or Finance is required.
• 3+ years of experience in model validation or front office model development roles is required.
• Strong verbal and written communication skills to interface with functional areas and write high-quality technical reports are required.
• Deep understanding of pricing and risk management models, including derivative pricing and stochastic calculus, is required.
• Deep understanding of standard statistical techniques for use in testing is required.
• Ability to implement benchmarking models in Python, R, or equivalent is required.
• Prior experience developing, validating, or working with models used in Asset Management is highly desirable (preferred).
• Hands-on experience with standard Machine Learning models, dedicated ML packages like TensorFlow, and data processing tools is highly desirable (preferred).