Superpedestrian is engineering the future of micromobility. The Superpedestrian team is composed of some of the most talented operations specialists, policy managers, designers and engineers, all focused on transforming the future urban mobility. Our scooters, called LINK, were designed to prioritize safety from the inside out, and our Superpedestrian team is dedicated to building meaningful local and city partnerships across the world. Join us

What you’ll do:
- Analyze data collected from IoT devices using state of the art data analysis tools to identify modeling opportunities
- Make use of state of the art machine learning techniques to create, maintain and improve statistical models of data collected from our IoT fleet
- Work with stakeholders to identify business value that can be delivered from models
- Contribute to infrastructure for collaboration with other Data Scientists working on other capacities at Superpedestrian

What you’ll bring:
- MS or equivalent experience in computer science, machine learning, digital signal processing or related field




- Fluency in Python with a focus on Data Science
- Experience with: Machine Learning frameworks such as Tensorflow or PyTorch, data science workbench such as JupyterLab, and Visualization tools such as Plotly, Matplotlib or bokeh.
- Basic understanding of web architecture (preferred)
- Enthusiasm for IoT systems

Why you'd want to join us:
- We’re different.
- We are born of engineers, not venture capitalists. Our control centre and test labs are located in Cambridge, Massachusetts, alongside MIT and Harvard University. We have some of the sharpest minds in the industry, and we hold more than 30 patents for our amazing technologies. None of our competitors come close.
- LINK is the result of eight years developing our artificial intelligence-driven safety platform, and two years designing a robust chassis and efficient powertrain to match. We take our time to get our technology, our operations and our recruitment

📌 Junior Data Scientist (Barcelona)
🏢 Superpedestrian
📍 Barcelona