Senior Applied Science Manager, AWS Analytics Engineering (AAE)

Key job responsibilities

• Define and drive the multi-year science, ML product, and software engineering vision and roadmap for ML-powered product analytics across AWS Products, Marketing, and Sales organization
• Build, lead, and develop a high-performing team of technical managers, applied scientists, and software engineers, including hiring top talent, managing performance, and growing careers through mentorship and promotion readiness
• Partner with senior AWS leaders (GM/VP level) to identify strategic, data-driven opportunities and translate business objectives into high-impact scientific initiatives
• Architect and guide enterprise-scale ML and agentic platform, including agentic system, knowledge representation, big data platform, deep learning, graph neural networks, reinforcement learning, causal inference, and forecasting models that predict business outcomes and enhance customer experiences
• Manage cross-functional science and software engineering team to build ML driven products that are scalable and leading industry best practices at the AWS scale and speed
• Invent, operationalize, and scale novel analytical frameworks and metrics that enable data-driven product growth and executive decision-making
• Communicate findings, conclusions, and strategic recommendations to technical and non-technical business leaders across AWS
• Mentor scientists and engineers, establish best practices for experiment design and model evaluation, and review technical artifacts to ensure quality
• Identify and champion new science opportunities that expand AAE’s impact across AWS, building the case for investment and driving adoption

About The Team

We are a team of scientists and software engineers supporting AWS product leaders to make high-impact decisions through sophisticated analytical frameworks, trusted data science methods, and scalable ML products. We come from diverse backgrounds in statistics, computer science, engineering, and business analytics. We specialize in the full end-to-end ML development process, including data ingestion, ETL, model development, and model deployment in production. We provide AI/ML services across decision science, ML products, multi-agent analytics systems, and data engineering platform.

High Impact Projects

We work on high-impact, high-visibility projects that directly influence AWS product roadmaps and senior leaders' decisions.

Basic Qualifications

• 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
• Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
• Experience building large-scale machine learning and AI solutions at Internet scale
• Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
• Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Preferred Qualifications

• 10+ years of practical work applying ML to solve complex problems for large-scale applications experience
• 5+ years of hands-on work in big data, machine learning and predictive modeling experience
• 5+ years of people management experience
• PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
• Experience in practical work applying ML to solve complex problems for large scale applications
• Experience working with big data, machine learning and predictive modeling