Amazon Robotics - Data Scientist Co-op - 2025

- Currently enrolled in a Master's or PhD program in Data Science, Mathematics, Statistics, Computer Science, Robotics, Engineering, Machine Learning, Computer Vision, Operations Research, Mathematics, Economics, Computer Science or a related quantitative field
- Degree program must be based in the United States with an expected graduation of December 2025 or later
- Must be eligible for and available for full-time (40 hours per week) internship based out of the assigned office location for the whole duration of the internship/co-op
- At least 1 year of relevant academic research or industry experience within relevant science disciplines such as Machine Learning, Applied Statistics, Computer Vision, Optimization, or related
- At least 1 year of experience working as a data scientist or a similar role involving data extraction, analysis, statistical modeling, and communication
- At least 1 year of experience using data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.)
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
- Excellent communication skills with ability to explain complex technical concepts to non-technical audience, while also efficiently interacting with deeply technical peers
- Understanding of data engineering and business intelligence
- Quantitative and qualitative data analysis experience with demonstrated impact to a business, a track record of creative problem solving, and the desire to create and build new processes
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience with Natural language processing (NLP) and working with large language models
- Experience with causal inference modeling
- Experience with A/B testing and data wrangling

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun.

Amazon Robotics is seeking students to join us for a 5-6 month internship (full-time, 40 hours per week) as Data Science Co-op.

Please note that by applying to this role you would be considered for Data Scientist spring co-op and fall co-op roles on various Amazon Robotics teams. The internship/co-op project(s) and location are determined by the team the student will be working on.

Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics



About the team
Amazon empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas.