At a Glance
- Tasks: Lead the development of fraud models and collaborate across teams to mitigate identity-verification fraud.
- Company: Join a leading financial services firm focused on innovative risk mitigation solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with significant impact on large-scale financial services.
- Why this job: Shape the future of fraud prevention with cutting-edge machine learning technologies.
- Qualifications: Advanced degree in a quantitative field and experience in fraud modelling or data science.
The predicted salary is between 63000 - 77000 £ per year.
In this role you lead the development and management of fraud models, including vendor solutions, to mitigate identity-verification fraud. You collaborate with Strategy, Technology, Product Management, Legal, Compliance, and governance bodies to maintain model risk standards. You will deploy advanced models, monitor performance, and provide audit-ready artifacts. You will translate complex model results for senior stakeholders and support cross-functional teams in governance and deployment activities. This is an opportunity to shape risk mitigation for large-scale financial services through data-driven, compliant ML solutions.
Responsibilities
- Develop and manage proprietary fraud models and perform due diligence for vendor models
- Validate model performance on internal data and ensure modelling choices fit portfolio and operational constraints
- Collaborate with platform engineers to support deployment
- Prepare governance and Model Risk Management packages with documentation and evidence
- Support independent validation and remediation of findings
- Monitor performance and stability (drift, calibration, population shifts, fraud-typology changes) and drive remediation
- Communicate design, trade-offs, results, and limitations to senior stakeholders
- Train and support downstream users on interpretation of model outputs
- Maintain audit-ready artifacts for internal audits and regulatory exams
- Provide timely, traceable responses to inquiries and keep documentation current post-deployment
Key requirements
- Advanced degree (MSc or PhD) in a quantitative or technical discipline
- Solid understanding of fraud modelling in financial organizations; credit modelling acceptable as transferable background
- Industry experience in applied data science with traditional statistics and ML models
- Proficiency in Python, SQL, and production-quality coding
- Experience with ML and data analysis toolkits (NumPy, Scikit-Learn, Pandas)
- Ability to leverage Generative AI tools to enhance productivity and problem-solving
- Strong written and spoken communication skills; team-oriented
Applied AI Machine Learning Vice President (Fraud Modelling) employer: JP Morgan Chase
Morgan is an exceptional employer, offering a dynamic work culture that prioritises diversity and inclusion while fostering employee growth through comprehensive coaching and development opportunities. As a global leader in financial services, we empower our teams to drive impactful product management and AI enablement, ensuring that every employee can contribute meaningfully to our clients' success in a collaborative environment located at the heart of the financial sector.
