Senior Data Scientist, Alexa For Shopping (Rufus)

Senior Data Scientist for Alexa For Shopping (Rufus) at Amazon. This role leads multi-agent orchestration and a self-improving agent system that extracts insights from unstructured data at scale and surfaces actionable metrics for product analytics.

Location

Seattle, WA (onsite)

Salary

USD 159,200 - 215,300 per yearly

Responsibilities

• Operate independently on problems that are not well-defined, framing research challenges across broad areas and delivering end-to-end solutions with significant product impact.
• Own the multi-agent topology (Planner Worker Reasoner Loop Controller) including inter-agent communication protocols and loop termination logic.
• Design and manage the context window strategy across agents.
• Own all system prompts, routing prompts, and chain-of-thought scaffolding across agents.
• Define what constitutes “better” across dimensions such as factual grounding, hypothesis novelty, evidence completeness, and reasoning coherence without scale ground-truth labels.
• Design the propagation of evaluation signals back into prompt updates and model routing decisions.
• Oversee schema grounding, sparse vector indexing, and domain-scoped kNN queries.
• Own embedding strategy, intent classification accuracy, and entity extraction quality.

Requirements

• 4+ years of data scientist experience
• 5+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab)
• Experience with statistical models such as multinomial logistic regression
• 5+ years of working with Data & AI related technologies, including AI/ML, GenAI, Analytics, Database, and/or Storage
• Python proficiency for statistical modeling, data manipulation (pandas, numpy, scipy), and scripting across ML pipelines and evaluation infrastructure
• Demonstrated experience extracting structured signals from unstructured text at scale (NLP pipelines, intent classification, entity extraction, or equivalent)

Technologies

• SQL, Python, R, SAS, Matlab, pandas, numpy, scipy
• AWS Bedrock, Strands SDK, LangGraph, CrewAI, AutoGen
• SageMaker, Neptune, Neo4j

Benefits

• Health insurance (medical, dental, vision, prescription)
• Basic Life & AD&D insurance and optional Supplemental life plans
• Employee Assistance Program (EAP)
• Mental Health Support
• Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave
• Sign-on payments
• Restricted stock units (RSUs)

Description

We are building an agentic intelligence system that transforms unstructured, noisy customer data into actionable intelligence for product analytics, guiding the evolution of the Amazon Shopping Customer Experience. The system surfaces metrics on demand and provides insights proactively, without a human analyst in the loop.

We tackle a challenging problem in the agent-driven data intelligence space by isolating insights from noise. This role will own end-to-end multi-agent system orchestration and context management, as well as a self-improving agent layer that improves over time without human intervention, with reliable signal extraction from unstructured data and proactive intelligence that identifies what matters before it is requested.

Our agentic system is already in production. The remaining gap is a mechanism to evaluate output quality, identify failures, and close the feedback loop automatically.

As Senior Data Scientist, you will own the multi-agent orchestration and the self-improvement system end-to-end. You will design the overall architecture to extract insights from unstructured data at scale, collaborate directly with the principal engineer, influence the technical roadmap, and partner with software development engineers.

Basic Qualifications

• 4+ years of data scientist experience
• 5+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab)
• Experience with statistical models such as multinomial logistic regression
• 5+ years of working with Data & AI related technologies, including AI/ML, GenAI, Analytics, Database, and/or Storage
• Python proficiency for statistical modeling, data manipulation (pandas, numpy, scipy), and scripting across ML pipelines and evaluation infrastructure
• Demonstrated experience extracting structured signal from unstructured text at scale (NLP pipelines, intent classification, entity extraction, or equivalent)

Preferred Qualifications

• Experience with multi-agent system evaluation and end-to-end ownership
• Production RAG or retrieval system experience, including embedding strategy, vector search, hybrid retrieval, and similarity threshold calibration
• AWS Bedrock or Strands SDK experience, or equivalent orchestration frameworks (LangGraph, CrewAI, AutoGen)
• Graph database experience (Neptune, Neo4j) including schema design, traversal queries, and knowledge graph construction
• Experience scaling NLP inference pipelines, including model sizing decisions, batching strategies, and endpoint optimization (SageMaker or equivalent)
• Business intelligence or analytics domain background including metric definitions, dimensional modeling, and causal inference
• Track record of publishing at peer-reviewed venues or presenting at industry conferences