Data Scientist , AMXL Science

Description

Are you passionate about applying machine learning, time series forecasting, and operations research to transform the delivery of heavy and bulky items for Amazon customers? Are you excited about working with large-scale operational data and developing models that drive real business impact? If so, the Amazon Extra Large (AMXL) Science team may be the right fit for you.

AMXL is Amazon's specialized business for delivering heavy and bulky items - appliances, furniture, fitness equipment, and mattresses - with a premium customer experience that includes room-of-choice delivery, at-home installations, and assembly services. In this role, you will leverage large-scale operational data to develop and deploy predictive models and optimization solutions that solve real-world logistics and fulfillment challenges, partnering closely with scientists, engineers, and business stakeholders.

• Apply machine learning, statistical modeling, time series analysis, and operations research techniques to build solutions for delivery routing, capacity planning, demand forecasting, workforce scheduling, and network optimization
• Analyze large-scale historical and real-time operational data to surface efficiency patterns, bottlenecks, and emerging trends across the AMXL network
• Develop, validate, and deploy models that improve cost-to-serve and customer experience
• Partner with cross-functional teams to implement data-driven strategies and measure impact
• Build scalable, automated pipelines for data ingestion, feature engineering, model training, and validation
• Monitor deployed model performance and communicate results through clear reporting on key operational and business metrics

You’ll be part of a small, collaborative team of scientists who move fast and care deeply about the problems they solve. A typical week might involve whiteboarding a new forecasting approach with a senior scientist, partnering with engineers to push a model into production, deep-diving into operational data to understand why a metric moved, or presenting your findings to business leaders who will act on them.

The work is high-visibility and high-impact. The models you build will directly influence how millions of heavy and bulky items reach customers.

The AMXL Science team is a worldwide group of data scientists, applied scientists, and product managers solving Amazon's most complex heavy bulky supply chain challenges. We build forecasting models, capacity planning systems, and optimization tools that directly impact millions of customer deliveries. Our culture values scientific rigor, measurable business impact, and clear communication. We start with baselines, earn complexity, and partner closely with operations to ensure our work drives real decisions.

You’ll tackle problems where logistics constraints demand creative, data-driven solutions - and see your models shape labor planning, routing, and customer experience at scale.

• Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
• 2+ years of data scientist experience
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• 1+ years of guiding and coaching a group of researchers experience
• 1+ years of working with or evaluating AI systems experience
• 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
• Experience applying theoretical models in an applied environment

• Ph.D. in Science, Technology, Engineering, and Mathematics (STEM)
• Knowledge of machine learning concepts and their application to reasoning and problem-solving
• Experience in Python, Perl, or another scripting language
• Experience in a ML or data scientist role with a large technology company
• Experience in defining and creating benchmarks for…