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Our team is the first in the world to use autonomous vehicles on public roads using end-to-end deep learning, computer vision and reinforcement learning. Leveraging our multi-national world-class research team we’re focusing on using data to learn more intelligent algorithms to bring autonomy for everyone, everywhere. We aim to be the future of self-driving cars, not vehicles that are told how to drive through hand-coded rules and maps, but ones which learn from experience and data.
We are a close knit team of researchers, engineers, scientists and more - some of us are straight out of school, others have worked on bleeding edge problems for some of the biggest tech companies on the planet - but we are all working together to solve autonomous driving.
To reimagine mobility for everyone, everywhere, we need a diverse, brave, intelligent, collaborative, dependable, inclusive and open-minded team that are courageous enough to challenge the status quo.
Join us for a challenge like none other!
Where you'll have an impact
As a Data Scientist in the Experimentation group, you will focus on generating robust, actionable insight that helps our product, data and research teams prioritise their efforts today and identify opportunities for tomorrow.
Rather than purely focusing on optimizing ML performance, Data Scientists focus on using experimental and causal inference methods to generate statistically-robust and highly interpretable findings: this often means using ML methods, but tailored to creating actionable insight. This is a fascinating opportunity to pioneer data science methodologies in a very complex and novel space in AV. This means you will:
Build the frameworks that best synthesise our complex video and simulation data, and use it to facilitate analytics-driven strategy from individual product teams all the way to the company level Formulate and iterate upon the performance metrics Wayve should focus on, to best measure success in an AV 2.0 world Combine real world experiment methods with offline causal inference techniques to account for the highly dynamic nature of autonomous driving on the road and help us reach statistical power faster
What you'll bring to Wayve
Essential
Desirable
What we offer you