Amazon Senior Data Scientist R2L Analytics 

United States, Washington, Bellevue 

79894336

Key job responsibilities
• Build sophisticated machine learning models and production pipelines to analyze complex logistics data
• Develop advanced AI solutions using Python, AWS tools, and emerging technologies like Large Language Models
• Synthesize information from diverse data sources to generate meaningful, actionable business insights
• Collaborate with cross-functional teams to translate complex technical findings into strategic recommendations
• Design and implement optimization strategies that enhance network performance and operational efficiency
A day in the life
As a Data Scientist in our R2L team, you'll immerse yourself in intricate data ecosystems, uncovering hidden patterns and opportunities that can revolutionize package delivery. Your daily work will involve exploring massive datasets, developing innovative analytical approaches, building production pipelines and transforming raw information into strategic intelligence.

- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 5+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Bachelor's degree and 8+ years of professional or military experience
- Strong background in data extraction, analysis, and communication
- Expertise in AWS tools and AI-focused technologies

- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience as a leader and mentor on a data science team
- Experience designing, building and managing data pipelines
- Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
- Experience working with scientists, economists, software developers, or product managers
- Experience working with data engineers and business intelligence engineers collaboratively