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Manager Model Risk Management information

What is the difference between Manager Model Risk Management vs Model Risk Analyst?

AspectManager Model Risk ManagementModel Risk Analyst
CredentialsTypically requires advanced degrees (e.g., MBA, Master's in Finance or Risk), certifications like FRM or CFAOften requires similar credentials, such as FRM or CFA, but may have less emphasis on managerial certifications
Work EnvironmentLeads teams, manages risk frameworks, and interacts with senior managementPerforms detailed risk analysis, supports model validation, and reports findings
Employer & Industry UsageCommon in banking, asset management, and financial institutionsFound in similar environments, often as a supporting role to managers

The Manager Model Risk Management oversees the entire model risk framework, manages teams, and interacts with senior stakeholders. In contrast, the Model Risk Analyst focuses on detailed analysis, validation, and reporting of models. Both roles require similar credentials but differ in scope and responsibilities.

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Manager Model Risk Management jobs near you

Risk Management - Model Risk Program Associate

JPMorganChase

Jersey City, NJ • On-site

Full-time

Re-posted 7 days ago

Job description

Job Summary:
JPMorgan Chase is one of the oldest financial institutions, providing innovative financial solutions globally. They are seeking a Risk Management - Model Risk Program Associate to design and build AI-native tools that transform the model risk lifecycle and enhance collaboration between risk professionals and model developers.
Responsibilities:
• Design, build, and deploy AI and LLM-based solutions that transform core MRGR processes and workflows during validation and governance.
• Work closely with MRGR teams to identify opportunities for AI to enhance and modernize model risk management practices and to understand the unique challenges and requirements of model risk governance.
• Remain current with emerging AI and LLM developments, get hands-on with new capabilities to understand their strengths and limitations, assess how they can be applied within MRGR workflows, and communicate actionable recommendations to stakeholders.
• Enable MRGR teams to effectively leverage AI tools and platforms in their day-to-day workflows, ensuring adoption is aligned with evolving best practices across the organization.
• Conduct independent model validation and governance activities to mitigate model risk, with a focus on AI/ML models, LLM-based applications, and Generative AI systems.
Qualifications:
Required:
• Master's or PhD degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Engineering, Economics, Finance, or a related field, with strong quantitative and analytical skills.
• Hands-on experience with applied AI/ML and LLM technologies, including prompt engineering, RAG architectures, agentic AI systems, context engineering, agent skills, MCP architecture, agentic harness, LLM evaluation and beyond.
• Strong foundation in statistics, econometrics, and machine learning techniques, with a deep understanding of model assumptions, limitations, explainability, and performance evaluation.
• Familiarity with LLM application tooling and frameworks (e.g., Claude Code, GitHub Copilot, LangChain, vector databases, embedding models, orchestration layers) and an understanding of how these components integrate in end-to-end deployed systems. Passion to stay at the forefront of how Generative AI is being operationalized in financial services and a desire to be a hands-on builder of AI solutions.
• Strong communication skills with the ability to present complex AI concepts to both technical and non-technical audiences.
• A risk and control mindset with the ability to ask incisive questions, assess the materiality of model issues, and escalate appropriately.
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.

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