Risk Management - Consumer and Community Banking Risk Product – Innovation Product Manager - Executive Director
On-site · Columbus, Ohio, United States
Job Summary
Executive Director, Risk Product Manager for Innovation in JPMorgan Chase’s Risk Management and Compliance. Lead cross-functional efforts across Product, Data Science, Engineering, Architecture, Security, and Risk/Model Governance to drive a multi-year innovation strategy for end-to-end risk products, establish KPIs and value narratives for leadership, and promote scalable, reusable capabilities (e.g., model registries, feature stores, canary/blue-green delivery, automated testing, and governance). Role emphasizes executive storytelling, roadmap execution, and embedding controls for fairness, explainability, and data quality, with a focus on advancing MLOps practices, governance, and regulatory alignment across consumer and community banking risk analytics.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
- 10+ years across Data Science, MLOps, Software/Platform Engineering, or related disciplines, including 5+ years delivering production ML at scale
- Deep hands-on familiarity with modern MLOps and platform practices: CI/CD and infrastructure as code (e.g., GitHub Actions/GitLab/Jenkins; Terraform/CloudFormation)
- Containerization/orchestration (Docker, Kubernetes) and service deployment patterns
- Model registries and feature stores; lineage and metadata management
- Automated testing for ML (data quality, unit/integration, performance, bias/fairness, explainability)
- Observability for data and models (drift, performance SLOs, alerting, rollback)
- Executive-level communication and storytelling skills—able to synthesize complex technical change into business outcomes and influence senior leaders
- Systems thinking and process design mastery; comfortable mapping current vs. target state and executing iterative change with measurable KPIs
- Cloud platform experience for ML services and batch scoring; cost management for ML workloads
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