As a Software Engineer - Model Risk Governance & Review - Analyst at JPMorgan Chase in Model Risk Governance & Review (MRGR) team, you will be developing tools for MRGR Analytics to improve efficiency and reduce duplication of effort, including resource management and cost optimization tools.
You will provide support for model reviewers and governance teams in building independent testing and efficiency tools. You will be delivering high-quality solutions by emphasizing the importance of data controls, testing and continuously seek input from users to align efforts with their objectives.
Job responsibilities
- Build data pipelines to fetch, validate, transform, and deliver data to applications, enabling reliable downstream analytics, automation, and reporting.
- Integrate on-going performance monitoring requirements for models into business applications through applied development work, primarily in Python using in-house frameworks.
- Leverage developer productivity tools (e.g., GitHub Copilot) to accelerate delivery, improve code quality, and enhance documentation and testing.
- Collaborate with cross-functional teams to identify opportunities for LLM integration and develop solutions that leverage LLM capabilities.
- Build intelligent solutions to support MRGR staff activities, including workflow automation and insight generation.
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and advanced applied experience
- A Bachelors or Masters degree in a Science, Technology, Engineering, or Mathematics discipline with significant exposure to computer programming.
- Proficient in Python and knowledge of Tornado web framework / TypeScript / React.
- Good understanding of software architecture, object-oriented programming and design patterns.
- Strong communication skills with the ability to interface with other functional areas in the firm on business requirements.
- Risk and control mindset: ability to think critically, assess user needs and create design solutions to meet user needs.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
Preferred qualifications, capabilities, and skills
- Experience in working with large data sets.
- Exposure to LLM integration and deployment in real-world applications.
- Experience in model risk management or financial services space.