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Known asset manager, metro location and mid-level seniority with specialized quant/ML requirements.
Role demands finance model risk and regulatory experience, so candidates from outside finance have limited fit.
Explicit 5-7 years, finance model validation, ML proficiency and regulatory experience make filters stringent.
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Lead and support validation of investment, financial, AI, and ML models including advanced language models like GPT, ensuring compliance with Model Risk Policy.
Develop and maintain the model inventory and risk assessment processes while engaging effectively with internal stakeholders such as model owners and developers.
Identify and communicate model issues, recommend remediation, and provide subject-matter expertise and guidance on model validation and regulatory compliance.
5-7 years of experience in quantitative modelling, model validation, or risk roles within financial services (investment banking or asset management preferred).
Advanced degree (Master's or Ph.D.) in Mathematics, Statistics, Computer Science, or related quantitative field preferred.
Proficiency in programming languages related to AI/ML such as Python, TensorFlow, or PyTorch, plus expertise in VBA and model programming languages (C++, Java, Python).
Work Experience Required: 5-7 years in relevant domain. Notice period: Not explicitly mentioned in the JD.
Experienced in rigorous validation of diverse model types including AI/ML and advanced language models within asset management or investment banking environments.
Capable of translating complex quantitative and technical findings into actionable recommendations for diverse stakeholders.
Demonstrated ability to manage collaborative relationships across risk and business functions while maintaining strong adherence to model governance and regulatory standards.