Senior Data Scientist
wayve
As a Data Scientist supporting AI Engineers, you partner with engineering teams to turn data into actionable direction for the Wayve AI Driver. You design experiments, define performance metrics, and evaluate real-world and simulated driving to improve safety, reliability, and commercial success. You communicate insights clearly to influence roadmap and prioritisation across time zones. This role offers hands-on impact in shaping AV2.0 and scalable autonomous driving tech, with cross-functional collaboration and a data-driven culture.
Pay / Benefits- competitive salary
- meaningful equity
- relocation support
- hybrid working
- learning and development budget
- comprehensive benefits
- Define and iterate performance metrics to guide engineering progress and business impact
- Design experiments and off-road measurements to meet customer product requirements while ensuring safety
- Investigate model training and inference bottlenecks affecting functionality
- Test and validate hypotheses to drive Wayve AI Driver improvements
- Summarise and visualise findings to support prioritisation and strategy
- Collaborate with cross-functional partners and communicate findings effectively
- 3+ years of experience in a Data Science role
- Fluent in querying and building large datasets with production-level SQL
- Experience designing robust real-world experiments (e.g., A/B tests) and evaluating test statistics
- Strong statistical foundations with appropriate distributions and hypothesis testing
- Proficient in Python with pandas, sklearn, statsmodels or scipy, or R with dplyr, caret or stats
- Skilled at summarising, visualising and communicating findings clearly
- Ability to influence team direction with actionable insights and prioritisation
- Comfort with asynchronous work across time zones and cross-functional partners
- Curiosity about building new things and contributing to AV2
- strong communication
- influence and stakeholder management
- curiosity and learning mindset
- SQL
- Python (pandas, sklearn, statsmodels, scipy)
- R (dplyr, caret, stats)
Reference: WJ-747_31168521