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About the Role
We are looking for a Data Scientist to help build a delivery business that's still taking shape. You will own measurement, modeling, and experimentation across how customers experience Amazon's drone-delivery service. Your work will span the full data-science toolkit, including designing and analyzing experiments, deep-diving customer-experience issues, building models, forecasting demand, and applying causal methods. You will translate rigorous analysis into clear, decision-ready recommendations and help define the right problems as much as solve them, with room to explore new methods and shape how we measure and improve as we scale.
Responsibilities
- Design and execute data science solutions using machine learning, statistical modeling, and generative AI techniques to address business problems where the approach is not immediately clear.
- Acquire, transform, and validate large, evolving operational and customer datasets; dive deep to investigate anomalies and data quality; and partner with data engineers to bring models and metrics into production.
- Design, run, and analyze experiments (A/B and quasi-experimental studies) to measure impact, size opportunities, and guide product and operational decisions.
- Deep-dive customer-experience issues and metric movements to identify root causes, and translate findings into clear, actionable recommendations.
- Communicate complex analyses to technical and non-technical audiences, earn the trust of senior leaders, and influence roadmap and prioritization decisions with recommendations.
- Own workstream end-to-end, from problem definition through delivery and ongoing measurement, partnering across data engineering, product, and business teams as the business scales.
Requirements
- 2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience.
- 2+ years of data querying languages (e.g. SQL, Hadoop/Hive) experience.
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
- Master's degree in a quantitative field, or Bachelor's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience.
- Experience applying theoretical models in an applied environment.
- Experience in Python, Perl, or another scripting language.
- Experience in a ML or data scientist role with a large technology company.
- Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.
- Experience applying causal inference methods (e.g., experimentation/A-B testing, quasi-experimental or observational causal methods such as DiD, IV, or causal DAGs).
- Experience designing, building, or reasoning over knowledge graphs (entity/ontology modeling, graph databases, or graph embeddings).
Skills
- Machine learning
- Statistical modeling
- Generative AI
- Data extraction
- Data analysis
- Communication
- SQL
- Hadoop/Hive
- Python
- Perl
- Experimental design
- Causal inference methods
- Knowledge graphs
- Entity modeling
- Ontology modeling
- Graph databases
- Graph embeddings
Location
- USA, WA, Seattle
Work Type
- Full-time
Experience Level
- 2+ years
- 3+ years
- 5+ years
Education Level
- Master's degree in a quantitative field
- Bachelor's degree in a quantitative field
Salary/Compensations
- 136,000.00 - 184,000.00 USD annually
Benefits
- Sign-on payments
- Restricted stock units (RSUs)
- Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
- 401(k) matching
- Paid time off
- Parental leave
About the Company
- Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
- Our inclusive culture empowers Amazonians to deliver the best results for our customers.
- If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Equal Opportunity
- Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.