Senior Data Scientist

Senior Data Scientist on the Model Integration & Release team at Wayve. The role owns the analytical layer that turns evaluation outputs into findings that improve both models and how they are measured, working across simulation, on-road experiment data, and internal evaluation tooling, in partnership with Validation, Data Science, and Product.

Responsibilities

Lead analysis of model and autonomous-vehicle performance data from simulations, offline evaluation, and on-road testing; Translate complex signals into clear recommendations for engineering teams; Investigate performance issues and apply statistical rigour to evaluation data; Identify where metrics, test coverage, or scoring logic could be improved; Define what deeper analysis means in practice and build the habits, tooling, and workflows that support it; Identify blind spots, inconsistencies, and gaps in simulation and offline metrics; Investigate on-road release-test findings and improve evaluation coverage and measurement; Perform experiment analysis and provide data-driven promotion recommendations for new driving models; Expand what "good" means beyond intervention rates using behavioural and operational signals; Partner with Data Science and Validation on how evaluation methods and ground truth are defined, implemented, and maintained; Support partner-facing quality investigations by quantifying and tracking issues raised through OEM QA workflows; Document findings and recommendations for a weekly release cadence and follow through so the same class of issue does not recur

Requirements

Strong analytical and investigative skills, able to move from a vague concern to a clear, evidence-backed conclusion; Hands-on experience with ML evaluation data, driving-performance metrics, or complex test results at scale; Experience applying statistical methods for A/B testing and experimentation, including confidence intervals, distributions, and sampling; Proficiency in Python or SQL and comfort querying and analysing large datasets; Ability to operate autonomously in a fast-moving environment, setting priorities within a broader goal and knowing when to solve issues directly versus escalate or partner; Clear written communication, turning messy investigations into concise, actionable recommendations for technical and non-technical audiences; Genuine curiosity about why a model behaves as it does and whether the right things are being measured

Nice to have

Experience in autonomous driving; Experience in robotics; Experience in safety-critical ML systems; Experience in simulation-based testing; Experience in on-road experiment analysis; Experience in OEM or partner validation workflows; Experience improving evaluation infrastructure and measurement methodology

Benefits

Salaries benchmarked against the market annually; Meaningful equity; Relocation support and visa sponsorship where applicable; Hybrid working and core hours; Chance to work hands on in vehicle workshops and labs; Learning and development budgets for training, conferences, and growth; Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, and team socials