Overview In this role you lead end‑to‑end ML/GenAI delivery within Moody’s AI Analytics group, guiding cross‑functional squads to transform risk insights into actionable outcomes. You will partner with data science, ML ops, and product teams to scale solutions across regions, balancing speed and governance. You’ll coach Agile practices, manage dependencies, and report on progress to senior stakeholders. This position offers the chance to help shape responsible AI use while improving efficiency and business impact.
Responsibilities - Oversee planning, execution, and release of multiple ML/Gen AI projects aligned with strategic objectives
- Manage dependencies across internal and external squads, ensuring smooth progress and timely delivery of product increments
- Facilitate quarterly planning and roadmap alignment with engineering and product teams
- Champion Agile methodologies (Scrum, Kanban) and coach cross-functional teams to embed Agile mindsets
- Facilitate ceremonies, retrospectives, and workshops to foster adaptability and innovation
- Engage with senior stakeholders across the organization, including analytical and technology teams
- Ensure transparency through dashboards, objectives and key results, and performance reporting
- Assist with running product pilot programmes, product rollouts, user feedback collection in the product management cycle
- Identify and mitigate delivery risks proactively
- Track quality metrics and drive continuous improvement
- Partner with data science, ML operations, and front-end teams to optimise release processes and reduce time-to-market
- Ensure alignment of delivery with product vision and business strategy
Key requirements - 3+ years of experience delivering AI/ML initiatives in complex environments
- Agile leadership with Scrum/Kanban coaching experience
- Backlog management and execution across multiple squads
- Strong stakeholder communication and governance/reporting skills
- Experience with Jira, Confluence, and agile estimation methods (story points, velocity, burndown)
- Working knowledge of data science workflows, coding concepts, AWS, and enterprise deployments (preferred)
- Experience coordinating delivery across regions and cross-functional teams (preferred)
- Familiarity with ML/GenAI tools and frameworks
- Knowledge of finance concepts and financial analysis
- Hands-on AI delivery experience and responsible AI awareness
- communication
- leadership
- cross-functional collaboration
- ML/GenAI delivery
- AWS
- data science workflows
