We build best-in-class solutions that enable data-driven decision making across our global DSP ecosystem. Our team partners with internal stakeholders, DSP owners, and cross-functional teams to deliver insights that drive operational excellence, business growth, and the success of small business owners in Last Mile delivery. Our work directly impacts customer experience, driver and station associate experience, DSP success, and Amazon's sustainable growth. The goal of Amazon's DSP organization is to exceed the expectations of our customers by ensuring that their orders, no matter how large or small, are delivered as quickly, accurately, and cost effectively as possible. To meet this goal, Amazon is continually striving to innovate and provide best in class delivery experience through the introduction of pioneering new products and services in the last mile delivery space. Come join us and help us make history We are seeking a passionate Data Scientist with deep expertise in optimization and causal inference to join our team.



You will work on some of the most challenging problems in DSP delivery planning and the business health space, applying data science rigor to improve how decisions are made and drive outcomes at scale.
Key Responsibilities
Develop Science Solutions for DSP Capacity Planning & Business Health: Design and implement data science solutions that optimize Delivery Service Partner (DSP) capacity allocation and business health measurement across the global DSP network. Leverage deep expertise in mathematical optimization and causal inference to identify opportunities for improving capacity planning models, volume share calibration methodologies, and business health measurement systems that drive partner sustainability.
Analyze Sentiment Risks & Business Health Metrics: Analyze sentiment risks and enhance algorithms that support DSP program management, including business health indicators, capacity reliability models, and partner viability frameworks tha

📌 Data Scientist II, WW DSP Analytics (Italia)
🏢 Vendita al dettaglio e all'ingrosso / Import-export
📍 Italia