Sr Manager, Data Science & Ai, R2l

Amazon Amazon · Big Tech · Bellevue, WA · Data Science

Senior Manager of Data Science & AI for Amazon's R2L (Retail Logistics) team, responsible for building and managing a team, defining the AI technical roadmap, and executing the Gen AI strategy to optimize supply chain and delivery operations. This role involves people leadership with deep technical expectations, influencing senior leaders, and raising the technical bar across the organization.

What you'd actually do

  1. Build and manage a team of Data Scientists and BI Engineers
  2. Define and drive the multi-year vision for Science and AI roadmap for R2L, aligning investments with business priorities to deliver measurable efficiency and customer experience improvements
  3. Define and execute the Gen AI strategy for R2L, identifying high-impact use cases for LLMs, agentic AI, and automation across operational workflows
  4. Influence VP and Director-level leaders through data-driven narratives, technical deep dives, and business impact framing
  5. Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions

Skills

Required

  • 11+ years of quantitative and qualitative data science/business intelligence with significant business impact experience
  • Experience with statistical modeling / machine learning
  • Experience developing, deploying and managing AI products at scale
  • Experience managing analytics, data science or technology teams, with a product or insight focus
  • Bachelor's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

Nice to have

  • Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
  • Masters Degree in Data Science or related field
  • Experience with generative AI, large language models, and agentic AI systems

What the JD emphasized

  • AI technical roadmap
  • Gen AI strategy
  • LLMs, agentic AI, and automation
  • data science and AI investments
  • AI products at scale
  • generative AI, large language models, and agentic AI systems

Other signals

  • leading and scaling the data science function
  • owning the AI technical roadmap
  • delivering data science and AI solutions
  • defining and executing the Gen AI strategy
  • identifying high-impact use cases for LLMs, agentic AI, and automation