Robotics - Data Science Intern ​/ Co-op - 2026

Robotics - Data Science Intern / Co-op - 2026

Are you passionate about data science? Do you want to solve real customer problems through innovative technology? Do you enjoy working on scalable research and projects in a collaborative team environment? Do you want to see your science solutions directly impact millions of customers worldwide?

At Amazon, we hire the best minds in technology to innovate and build on behalf of our customers. Customer obsession is part of our company DNA, which has made us one of the world's most beloved brands.

We're looking for current Master's and PhD students with a passion for robotic research and applications to join us as Robotics Data Scientist Intern/Co-ops in 2026. Our robotics teams are looking for students with a specialization in robotics, data science, computer vision, large language models, visual language models, statistics, machine learning, causal inference, deep learning, artificial intelligence, applied generative AI, operations research, data analysis, predictive modeling, and more.

By applying to this role, you will be considered for Robotics Data Science Intern/Co-op (2026) opportunities across various robotics teams at Amazon with different research focus. Internship positions are available for multiple locations, durations (3 to 6+ months), and year‑round start dates.

• Design and implement state‑of‑the‑art solutions for never‑before‑solved problems.
• Collaborate closely with other research and robotics experts to design and run experiments, research new algorithms, and find new ways to improve Amazon Robotics analytics to optimize the customer experience.
• Partner with technology and product leaders to solve business problems using scientific approaches.
• Build new tools and invent business insights that surprise and delight customers.
• Work to quantify system performance at scale, and to expand the breadth and depth of our analysis to increase the ability of software components and warehouse processes.
• Work to evolve our library of key performance indicators and construct experiments that efficiently root cause emergent behaviors.
• Engage with software development teams and warehouse design engineers to drive the evolution of the Amazon Robotics system, as well as the simulation engine that supports our work.

Learn more about Amazon Robotics and our initiatives at Amazon Robotics and Amazon Million Robots AI Foundation Model.

• 18 years of age or older.
• Currently enrolled in a Master's or PhD program in Data Science, Mathematics, Statistics, Computer Science, Robotics, Engineering, Machine Learning, Computer Vision, Operations Research, or a related quantitative field.
• Eligible for and available for a 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 one year of relevant academic research or industry experience within relevant science disciplines such as machine learning, applied statistics, computer vision, optimization, or related fields.
• At least one year of experience working as a data scientist or a similar role involving data extraction, analysis, statistical modeling, and communication.
• At least one year of experience using data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, MATLAB).

• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
• Excellent communication skills with the ability to explain complex technical concepts to a 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 on 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,…