• Lead end-to-end coordination for complex, multi-team initiatives that span AI models, infrastructure, experimentation, and product integration • Define and track milestones, manage dependencies, and ensure alignment across engineering, applied science, product, and infrastructure partners • Operate effectively in evolving problem spaces • Work across multiple EMs, PMs, data scientists, and applied science leads • Build and refine lightweight program rituals that improve execution consistency and visibility for AI-heavy launches • Connect the dots between product-facing teams and foundational/platform teams • Produce concise status updates, decision documents, and alignment artifacts for stakeholders

• Lead programs that enhance lab efficiency, reliability, and scalability. • Manage the rollout of a centralized lab infrastructure reservation system. • Program-manage the rollout of engineering lab managed services and lab solutions. • Drive modernization across engineering labs and lead the Management of Change (MoC). • Track and communicate operational metrics, dashboards, and KPIs. • Collaborate with lab software engineers to integrate automation frameworks.

• Contribute to the product strategy and roadmap for the portfolio of applications • Identify the order of importance and urgency among individual projects, portfolios and operational tasks to plan milestones, schedules and resources • Ensure that projects goals, objectives, milestones and deliverables are achieved on schedule and within budget • Develop status reporting and communicate effectively and proactively to all levels of the organization regarding status, schedules, risks, issues, etc. • Proactively identify and communicate risks or issues that might impede assigned projects, and develop mitigation plans or solutions to resolve • Develop and maintain strong relationships with key executives, senior leaders, stakeholders, and team resources throughout the organization to achieve project objectives and deliverables • Define, manage, and improve project management processes and champion ongoing process improvement initiatives to implement best practices for Agile Project Management • Collaborate with business stakeholders and application owners to develop test management plans; test scenarios, defect capturing, test status reporting, and approvals • Collaborate with business stakeholders and application owners to develop change management plans and track change management activities as part of an overall project plan • Contribute to a team environment that encourages collaboration, ongoing feedback, and participation throughout the Finance Engineering teams.D

• Lead strategic programs across the Data, AI, and Analytics domains, delivering high-impact initiatives in platform modernization, machine learning deployment, and data governance. • Partner with Data Engineering, Data Science, and Analytics leadership to define and sequence the Data roadmap, aligning scope and priorities with company objectives while driving effective prioritization and trade-off decisions across features, tech debt, and platform initiatives in an inherently ambiguous, fast-evolving environment. • Drive end-to-end delivery across multiple engineering squads, managing complex dependencies across data pipelines, modeling workflows, and analytics infrastructure — ensuring smooth delivery from ingestion to insight. • Drive the operationalization of AI models into production in partnership with MLOps and engineering teams, balancing innovation with compliance and performance. • Collaborate with Product and Business teams to ensure data and AI solutions drive measurable outcomes — from credit decisioning to fraud detection to customer engagement. • Drive delivery across third-party vendors and financial partners, ensuring integrated solutions meet program milestones, quality standards, and business objectives while proactively managing risks to scope and timeline. • Build strong partnerships across Security, Infrastructure, Compliance, Legal, Finance, and Risk to deliver efficient, resilient, and capital-effective solutions. • Champion Agile and CI/CD practices, elevating execution quality through repeatable, scalable delivery processes. • Act as a trusted advisor to senior leadership, providing clear, actionable communication on program health, risks, trade-offs, and dependencies. • Mentor TPMs and cross-functional partners, fostering a culture of technical excellence, ownership, and trust.