Amazon Data Scientist-Robotics Performance & Insights 

United States, Massachusetts 

159158729

We are seeking an innovative and impact-driven Data Scientist to design, build, and deploy advanced analytics and Generative AI solutions. You will be at the forefront of transforming our global support model by developing predictive insights, automating performance intelligence, and powering scalable decision-making across a growing fleet of AR-supported sites.Key job responsibilities
- Develop and deploy ML models to predict AR network risks based on telemetry, support tickets, and operational data.

- Bachelor's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 6+ years of data scientist experience
- 3+ 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
- 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
- Master's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 3+ years of experience developing and deploying predictive models in production environments.
- Hands-on experience with GenAI technologies (e.g., LangChain, transformers, LLM fine-tuning, prompt engineering).
- Expertise in Python, SQL, SageMaker (or equivalent ML infra), and data pipeline frameworks.
- Strong communication skills with experience translating complex findings into actionable business insights.
- Experience working in large-scale operational or hardware network environments (e.g., robotics, fulfillment, manufacturing) is a plus.