About the job
The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes! We are looking for a Data Scientist to join our team and solve some of the most complex business problems!
Responsibilities
- Work with product managers, engineers, other scientists, and leadership to identify and prioritize complex problems.
- Interview stakeholders to gather business requirements and translate business problems into data science or analytical problems
- Design, develop, and evaluate highly innovative statistics and ML models
- Guide and establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Proactively seek to identify business opportunities and insights and provide solutions to shape key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams.
Qualifications
Minimum
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- 2+ years of data scientist experience
- 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
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of working with or evaluating AI systems experience
- Experience applying theoretical models in an applied environment
- Experience effectively communicating complex concepts through written and verbal communication
Preferred
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team, cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions