Senior Delivery Manager, Data & Models

Role overview Own delivery planning and coordination for data and model initiatives from intake through deployment and ongoing maintenance. You will establish delivery practices for work that spans technical, credit, risk, and compliance teams, keeping dependencies, sequencing, and governance clear as priorities evolve.

Responsibilities - Build and maintain roadmaps with milestones, dependencies, and sequencing across data and model work. - Provide leaders and partner teams with a current view of initiative status, risks, owners, and next steps. - Coordinate across data engineering, data science, credit, risk, and compliance; surface dependencies early and drive resolutions. - Create delivery playbooks and clear handoffs for model development, validation, deployment, policy updates, and approvals. - Prepare model governance reviews so required information and approvals are ready at the right stage. - Establish delivery practices for data platforms, pipelines, data products, and data quality remediation. - Improve planning and execution using delivery metrics and retrospectives, and guide colleagues as the practice develops.

Requirements - At least five years of program or project delivery experience, ideally in financial services, fintech, or another data-heavy setting. - Experience leading concurrent initiatives across at least three cross-functional teams, including technical teams. - Working knowledge of data and model lifecycles, including engineering, validation, deployment, and monitoring. - Experience with model governance, model risk management, or formal review and approval in a regulated environment. - Ability to create delivery processes, documentation, reporting, and handoffs that teams sustain. - Clear communication, sound prioritization, and judgment about when to resolve issues directly or escalate them. - Willingness to travel approximately four or more times per year for in-person collaboration.

Nice to have Direct experience with second-line oversight or bank regulator expectations for model risk, such as preparing for validation or regulatory examinations; experience delivering data platforms or pipelines.