Own measurement, modeling, and experimentation for Amazon’s drone-delivery service, turning large-scale data into decision-ready recommendations.

Design and deliver data science solutions using machine learning, statistical modeling, and generative AI when the best approach is not immediately obvious
Acquire, transform, and validate large and evolving operational and customer datasets
Investigate anomalies and data quality, partnering with data engineers to productionize models and metrics
Design, run, and analyze A/B tests and quasi-experimental studies to quantify impact and opportunity size
Perform customer-experience deep dives to identify root causes behind metric movement, connecting outcomes to drivers and translating findings into clear recommendations
Communicate complex analysis to technical and non-technical audiences, influencing roadmap and prioritization with recommendations
Own workstream delivery end-to-end, from problem definition through ongoing measurement, in partnership with data engineering, product, and business teams as the business scales

2+ years in a data scientist (or similar) role with experience in data extraction, analysis, statistical modeling, and communication
2+ years experience with data querying languages such as SQL and Hadoop/Hive
3+ years in ML/statistical modeling analysis using tools and techniques, including experience with parameters that affect performance
Master’s degree in a quantitative field, or Bachelor’s plus 5+ years in a quantitative field (e.g., statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science)
Experience applying theoretical models in an applied environment

Experience in Python, Perl, or another scripting language
Experience in an ML or data scientist role at a large technology company
Experience developing experimental and analytic plans, using strong baselines, and accurately determining cause-and-effect relationships
Experience applying causal inference methods, including experimentation/A-B testing and quasi-experimental or observational causal approaches such as DiD, IV, or causal DAGs
Experience designing, building, or reasoning over knowledge graphs (entity/ontology modeling, graph databases, or graph embeddings)

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

Review model performance metrics before working sessions with engineers to refine a data pipeline
Prototype a new machine learning approach, run experiments, and compare results against baseline models
Present preliminary findings to business partners and translate statistical outputs into plain-language recommendations
Join team discussions, scientific reviews, and mentoring conversations

Location: Seattle, WA (onsite)

Salary: USD 136,000 - 184,000 per yearly

Minimum Experience: 2 years

Data Scientist II

Job Description