Overview:
In this role you drive strategy and execution for fraud decisioning and automation programs within Apple’s SDS team. You collaborate with data scientists, engineers, and operations to deliver analytics-driven solutions that mitigate fraud, grow revenue, and streamline operations. You’ll balance priorities, manage complex projects, and foster partnerships across Apple to deliver impactful results. This is a chance to shape cross‑functional programs in a high‑stakes domain and contribute to Apple’s mission of delivering exceptional products and experiences. Compensation / Benefits Comprehensive medical and dental coverage retirement benefits stock programs for shareholders tuition reimbursement for education relocation support discounted products and free services
Responsibilities:
Collaborate with data scientists, engineers, analysts, and PMs to align on strategy and delivery Identify new business opportunities and translate them into analytic solutions with clear roadmaps Prioritize work considering impact, cost, resources, timelines, and risks Provide day-to-day project management and maintain visibility with leadership Engage with engineering and analytics on system design, fraud logic, metrics, and release lifecycle Lead cross-functional initiatives with distributed teams through influence and communication
Key requirements:
BS / MS in analytical/technical field or equivalent experience 5+ years of program management experience Ability to simplify complex problems and propose innovative solutions Strong risk management, tracking, and mitigation skills Experience leading large cross-functional technical/analytic projects Ability to align schedules across distributed teams via collaboration and influence Proven ability to motivate others and build partnerships Curiosity and continuous self-improvement mindset Excellent interpersonal skills across levels Experience in business discovery and requirements definition strong interpersonal skills ability to influence and align diverse stakeholders curiosity and self-improvement fraud detection/response machine learning or data analytics data systems design and analytics