Applied Scientist, Prime Video Science

We're looking for an Applied Scientist to help build the next generation of these models.

As an Applied Scientist on this team, you will build machine learning and deep learning models on large-scale global data to simulate customer behavior across the business. Ideally you bring experience with reinforcement learning, causal inference, and/or the design of agentic AI systems. You will partner closely with business, finance, engineering, and science stakeholders to take ideas from concept and prototype through to production.

The candidate should have strong communication skills and the ability to translate data-driven findings into actionable insights. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and the ability to work in a fast-paced and ever-changing environment.

Key job

responsibilities - Build models that simulate customer behavior to answer counterfactual "what-if" questions that guide major content and product investment decisions. - Apply deep learning, reinforcement learning, causal inference, and experimental design to large-scale customer data to model how customers respond to change. - Design and prototype agentic AI systems and other novel ML approaches and research new methods to improve the accuracy and scale of our models. - Validate and calibrate models against real-world randomized experiments, and partner with software engineers to deliver scalable, production-ready systems. - Translate model outputs into clear recommendations and communicate results to business, finance, and science stakeholders through both technical papers and business-facing documents.

About the team The Prime Video Science team is a multidisciplinary group of applied scientists, data scientists, economists, and engineers. We take on some of the hardest research questions in the business, and our work carries visibility up to the CFO/CEO level. We pursue ambitious research at the intersection of machine learning, AI, and causal inference, turning that research into innovations that improve customer experience and strengthen business profitability.

Few science teams get to work on problems this hard and this impactful; if that combination excites you, we'd love to talk. - 3+ years of building machine learning models or developing algorithms for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language