Senior Applied Scientist

Amazon hires a Senior Applied Scientist in Tokyo to build AI-native science platforms that scale rigorous analytics to decision-makers. The work spans multi-agent AI frameworks, causal inference automation, generative AI and simulation engines.

The scientist leads the design and development of platforms that automate the whole science lifecycle from hypothesis to causal analysis, model validation and deployment into production. The role includes building shared knowledge infrastructure such as feature stores, experiment registries and model leaderboards, creating evaluation frameworks including seller simulations that test models and interventions on synthetic populations before launch, and connecting validated insights to seller-facing actions in downstream systems. The scientist works with cross-functional partners including product teams.

Applicants need a PhD, or a master's degree plus five or more years of building machine learning models for business applications, and knowledge of programming languages such as C/C++, Python, Java or Perl. Preferred are a PhD in a quantitative field, experience with large-scale machine learning systems including profiling, debugging and scalability, and business-level Japanese or above (JLPT N1 or higher).