Senior Python Developer - Quant Models AI Automation, Vice President

In this role you will design and build Python-based services and tooling to automate the end-to-end quantitative model lifecycle for market and credit risk. You’ll work within Risk Technology on a multi-year initiative to enable AI-assisted model documentation, testing, and data analysis, delivering production-grade solutions. You’ll collaborate with quants, validators, data engineers, and program leadership to translate automation needs into robust workflows. This position offers impact by modernizing risk model pipelines and governance through scalable engineering and AI enablement.

• Design and maintain Python-based services, pipelines, and tools for automating the model lifecycle across risk families
• Build and operate automated testing and validation frameworks with orchestration, benchmarking, and reporting
• Develop data analysis and reconciliation tooling for large-scale risk datasets ensuring data quality, lineage, and traceability
• Contribute to model lifecycle management tooling including inventory, workflow orchestration, approvals, and audit-ready evidence generation
• Implement AI/ML components within the workflow for documentation generation, data quality checks, and workflow assistance
• Integrate AI tooling into a controlled, auditable production environment with testing, monitoring, and governance controls
• Collaborate in a cross-functional agile team and promote engineering best practices; mentor junior developers and participate in design reviews

• STEM degree (Computer Science, Engineering, Mathematics, Statistics, Physics, or related)
• Professional software development experience with deep Python expertise and data/engineering ecosystem (pandas, NumPy, FastAPI, orchestration tools)
• Proven track record delivering production-grade automation, data pipelines, or testing frameworks in a complex enterprise environment
• Solid AI/ML knowledge with practical experience in libraries and/or LLM-based development
• Strong experience with test automation, CI/CD, Git, code reviews, and containerization
• Experience working with large datasets, data quality checks, and SQL; familiarity with enterprise data platforms
• Ability to work in a cross-functional, global team and communicate with non-technical stakeholders
• Preferred familiarity with quantitative risk models and the model lifecycle, governance in banking
• Experience with workflow orchestration platforms, cloud environments (AWS/Google Cloud), and containers (Docker/Kubernetes)
• Background in quantitative finance, statistics, or data science is a plus
• Experience mentoring engineers and leading small technical workstreams

• collaboration
• mentorship
• clear communication
• Python
• pandas
• NumPy