Applied AI VP: Fraud Modelling & Identity Verification

JPMorgan Chase & Co.; Greater London; On-site; GBP 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. in London is seeking an Applied AI Machine Learning VP (Fraud Modelling) to lead development and governance of fraud models within ICB Risk Modelling.

You will drive advanced solutions for identity verification fraud and oversee model deployment with platform engineers. You will collaborate with Strategy, Technology, Product Management, Legal, Compliance, Business Management and Model Governance to ensure models meet governance standards and regulatory requirements,

Qualifications

• Advanced degree in a quantitative/technical discipline.
• Solid understanding of fraud modelling in financial organisations and regulatory considerations.
• Experience in applied data science and ML techniques with traditional and ML models.
• Proficiency in Python/SQL with production-quality code and data analysis.

Responsibilities

• Develop and manage proprietary fraud models and validate vendor models.
• Prepare governance and Model Risk Management packages and support independent validation.
• Monitor performance, drift, and calibration; drive remediation actions.
• Communicate design, trade-offs, and results to senior stakeholders.
• Maintain audit-ready artifacts and respond to inquiries for audits.

Skills

Advanced degree (MSc/PhD)

Fraud modelling

Python

SQL

NumPy

Scikit-Learn

Pandas

Generative AI

Communication

Education

MSc or PhD in quantitative/technical field

Tools

Python

SQL

NumPy

Scikit-Learn

Pandas

Job description

JPMorgan Chase & Co. in London is seeking an Applied AI Machine Learning VP (Fraud Modelling) to lead development and governance of fraud models within ICB Risk Modelling.

You will drive advanced solutions for identity verification fraud and oversee model deployment with platform engineers. You will collaborate with Strategy, Technology, Product Management, Legal, Compliance, Business Management and Model Governance to ensure models meet governance standards and regulatory requirements,