Senior Model Risk Manager - AI/ML
WFA Digital Insight
The demand for skilled model risk managers in fintech has surged, with a 25% increase in job postings over the past year. As AI transforms financial services, companies like Mercury are seeking experts who can navigate the complexities of model risk management. With the rise of generative models and autonomous systems, the need for forward-thinking risk managers has never been more pressing. Candidates should be prepared to showcase their technical expertise and ability to communicate complex ideas to stakeholders. Before applying, it's essential to understand the evolving landscape of model risk management and the unique challenges it presents.
Job Description
About the Role
Mercury is at the forefront of fintech innovation, and as a Senior Model Risk Manager - AI/ML, you will play a critical role in shaping the company's approach to model risk management. The successful candidate will be responsible for defining and implementing a comprehensive model governance framework, ensuring the integrity and reliability of Mercury's AI/ML models. This is a unique opportunity to join a pioneering company and contribute to the development of a new standard for model risk management in the fintech industry.The role will involve close collaboration with data scientists, engineers, and product teams to identify and mitigate potential risks associated with AI/ML models. The ideal candidate will have a deep understanding of machine learning and AI systems, as well as experience in model validation and risk management.
As a Senior Model Risk Manager - AI/ML, you will be part of a dynamic team that is passionate about innovation and excellence. You will have the opportunity to work on complex and challenging projects, and contribute to the growth and success of the company.
What You Will Do
- Develop and maintain a comprehensive model governance framework for AI/ML models
- Perform independent validation of predictive ML models, generative AI systems, and agentic workflows
- Assess risks in LLM-powered applications, including RAG pipelines, tool use, autonomy boundaries, human oversight, and hallucination risk
- Identify and document model limitations, failure modes, and emerging AI risks
- Serve as a trusted advisor to data scientists, engineers, product teams, and risk partners throughout the AI/ML lifecycle
- Evaluate new AI use cases for regulatory implications, materiality, and governance requirements
- Develop and maintain AI-enabled automation tools to improve the speed, scale, and effectiveness of model governance and validation workflows
- Modernize the MRM function to operate effectively in a fast-moving AI environment
- Champion MRM as a strategic enabler of safe and scalable AI/ML adoption
What We Are Looking For
- 5+ years of experience in model risk management, model validation, or a related field
- Deep understanding of machine learning and AI systems, including generative models and autonomous agents
- Experience in model validation and risk management, including data, assumptions, methodology, testing, and monitoring
- Strong understanding of regulatory requirements and industry standards for model risk management
- Excellent communication and interpersonal skills, with the ability to communicate complex ideas to stakeholders
- Experience working in a fast-paced and dynamic environment, with the ability to adapt to changing priorities and deadlines
- Strong analytical and problem-solving skills, with the ability to identify and mitigate potential risks
Nice to Have
- Experience with cloud-based technologies and agile development methodologies
- Knowledge of programming languages such as Python, R, or SQL
- Experience with data visualization tools and techniques
- Certification in model risk management or a related field
Benefits and Perks
- Competitive salary and benefits package
- Opportunity to work on complex and challenging projects
- Collaborative and dynamic work environment
- Professional development and growth opportunities
- Flexible working hours and remote work options
- Access to cutting-edge technologies and tools
- Recognition and reward for outstanding performance
How to Stand Out
- Be prepared to showcase your technical expertise in model risk management and AI/ML systems
- Highlight your experience in model validation and risk management, including data, assumptions, methodology, testing, and monitoring
- Demonstrate your ability to communicate complex ideas to stakeholders, including data scientists, engineers, and product teams
- Emphasize your understanding of regulatory requirements and industry standards for model risk management
- Be prepared to discuss your experience working in a fast-paced and dynamic environment, and your ability to adapt to changing priorities and deadlines
- Showcase your analytical and problem-solving skills, including your ability to identify and mitigate potential risks
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