• Manages portfolio across multiple concurrent data center design projects. • Responsible for delivering revenues assigned. • Consistently delivers profit margins planned. • Monitor program performance including schedule, budget, staffing, and risk. • Utilize earned value management to assess work progress against the baseline. • Identify and resolve program-level constraints impacting delivery. • Ensure consistency of execution across multiple projects and clients. • Support Design Managers and Strategy Site Managers in maintaining successful delivery. • Participate in client meetings, presentations, and program reviews. • Lead change management process for internal and external changes. • Assist in managing client expectations and overall client experience. • Exchanges information on sensitive matters and works to build consensus across teams and departments. • Completes assigned work independently. • Travel as needed for project-related activities such as client meetings and site visits. • Apply for and obtain AECOM Project Manager certification within 1 year of start date.

• Lead digital delivery across the hyperscale data center portfolio • Implement and enforce project-level BIM standards, execution plans, and workflows • Oversee U.S. BIM staff and global enterprise-capabilities partners • Drive timely correction of deficiencies and ensure compliance with contractual requirements • Conduct regular QA reviews • Perform hands-on Revit production as required • Report on BIM KPIs, compliance metrics, and deliverable status to project leadership

• Model Development: Prototype, evaluate, and help productionize machine learning models for fraud detection; own their ongoing monitoring and retraining cycles. • Experimentation: Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction. • Risk Assessment: Size fraud typologies across our product lines to inform prioritisation and investment decisions. • System Maintenance: Build and maintain anomaly detection systems to surface novel fraud vectors before they scale. • Cross-Functional Collaboration: Work closely with fraud operations, engineers, product managers, and data analysts to translate model outputs into real-world mitigations.

• Own the supply side of Protege's data platform • Define the stages, validation gates, and quality checks that data passes through • Own the product decisions around metadata generation • Define what 'catalog-ready' means and build the tooling that enforces it • Work with vertical stakeholders to translate their requirements into platform-level standards