Who are we?
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 focusing on using black-box models to optimize ML performance, DS focus on using experimental and causal inference methods to generate statistically-robust and highly interpretable findings. 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:
- Comfortable querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
- Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
- Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
- Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
- Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
- Track record of influencing team direction through your findings
- A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
- Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
- Track record of promoting statistical rigour and experimental best practices in your prior roles.
- Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
- Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
- Experience working in a fast-moving tech company or startup.
What we offer you
- Attractive compensation with salary and equity
- Immersion in a team of world-class researchers, engineers and entrepreneurs
- A unique position to shape the future of autonomous driving and to tackle the biggest challenges of our time
- Bespoke learning and development opportunities
- Relocation support with visa sponsorship
- Flexible working hours - we trust you to do your job well, at times that suit you and your team
- Private onsite chef, in-house bar, lots of socials, and more!
Wayve is built by people from all walks of life. We believe that it is our differences that make us stronger, and our unique perspectives and backgrounds that allow us to build something different. We are proud to be an equal opportunities workplace, where we don't just embrace diversity but nurture it - so that we all thrive and grow.