Simbe Robotics, San Francisco Bay Area
Simbe is looking for a Data Analytics & Data Science Intern to join our Data Science & Analytics team and help turn large-scale retail and robot data into reliable insights, analytical products, and internal tools.
This internship is designed for students who want hands-on experience working with production data systems and solving real analytical problems at the intersection of data engineering, analytics, AI, and robotics.
Internship Program Structure Interns join Simbe as part of a structured cohort and work full time from our Burlingame, California headquarters.
We do not believe in creating busywork for interns. Your project will be selected closer to your start date based on active team priorities so that you can contribute to meaningful work alongside our full-time team.
Simbe Values: R. E. T. A. I. L.
Result Driven – We are customer-centric and results-driven. We strive to create immense value for our team, partners, customers, and investors.
Empathetic – We are sensitive and mindful. We support each other in challenging times, both professionally and personally.
Transparent – We value open communication internally, and with our partners and customers. We are receptive to feedback.
Agile – We are eager to learn and adapt quickly to changes and customer needs.
Innovative – We are bold and innovative, with an intense focus on product design, user experience, and customer value.
Leaders – We strive for excellence. We are accountable, the best at what we do, and leaders in our field.
Simbe is building the AI-powered operating system for physical retail. Our autonomous robots and multimodal data collection systems turn complex, constantly changing stores into accurate, actionable intelligence for leading retailers around the world. Simbe combines robotics, computer vision, machine learning, data infrastructure, and analytics to help retailers improve shelf availability, inventory accuracy, store execution, and operational decision-making.
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Source: the Simbe Robotics Lever job board. We last checked this job 2 h ago. We first saw it 4 days ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.