Data Scientist, Robotaxi Performance & Capability

Wayve • Sunnyvale, CA

13h • Hybrid

About The Position

The Data Scientist will work within Wayve’s Product Architecture & Safety team to assess when the AI Driver is ready for fully driverless Robotaxi service. Working with Model Development, Behavioural Validation, Safety and Robotaxi Engineering, the role turns real-world driving, validation and operational data into evidence of current capabilities, limitations and areas for improvement. The analysis will inform development priorities and help measure progress toward a safe, reliable and scalable driverless service.

The role involves hands-on analysis of complex datasets using Python and SQL, investigating driving behaviours and operational events, and presenting findings to guide product and engineering decisions. The Data Scientist will develop metrics, performance baselines and dashboards; use statistical methods to assess rare events and uncertainty; and contribute evidence to product-readiness reviews. The work covers driverless readiness, system capability gaps, the full Robotaxi experience, service reliability and challenging driving scenarios.

The position is available on a hybrid basis in Sunnyvale or remotely within the USA. Wayve describes a hybrid working model that combines collaboration in its offices with remote work. The role offers substantial ownership in a company where processes and ways of working are still developing.

Requirements

• At least three years of relevant experience in data science, automotive data analysis or a related field; deeper experience is expected for senior-level opportunities.
• Hands-on experience with Python, SQL, statistical analysis and tools for exploring and visualising large datasets.
• Ability to turn ambiguous real-world problems into measurable questions, useful KPIs and practical analytical approaches.
• Experience analyzing complex systems, uncovering performance limitations and translating findings into product or engineering improvements.
• Understanding of statistical confidence, rare-event analysis, performance distributions and trends.
• Ability to work independently with incomplete data, make reasonable assumptions and refine an approach as new evidence emerges.
• Clear communication skills, including the ability to explain findings and their limitations to engineering, product and leadership stakeholders.

Nice To Haves

• Experience in autonomous driving, ADAS, robotics, mobility services or another complex physical system.
• Familiarity with vehicle dynamics, driving behaviour, safety-critical events or operational reliability.
• A relevant master’s degree or PhD in Physics, Statistics or Mathematics, particularly focused on traffic systems, autonomous driving deployment or urban mobility.

Responsibilities

• Analyze real-world driving, validation and operational data to assess driverless readiness and identify performance gaps.
• Investigate driving behaviours and operational events to understand where, why and how often the system falls short of driverless service expectations.
• Quantify the operational impact of performance gaps and track whether they are closing.
• Distinguish issues that may be addressed through better model performance from those requiring additional system or product capabilities.
• Build practical metrics, performance baselines and dashboards to track progress across model, software and product releases.
• Apply statistical methods to assess rare events, quantify uncertainty and distinguish meaningful improvements from noise.
• Define metrics for remote assistance, passenger pickup and drop-off, passenger interactions, vehicle readiness and recovery from operational disruptions.
• Measure intervention demand, mission completion, recovery time and vehicle availability to assess service reliability.
• Investigate safety-critical interventions, unnecessary stops, stuck scenarios and manoeuvre execution across roads and operating conditions.
• Collaborate across Wayve to translate findings into development priorities, targeted validation and improved data collection.
• Contribute to product-readiness reviews by presenting evidence of progress, remaining limitations and confidence in conclusions.
• Communicate analytical findings and limitations to engineering, product and leadership stakeholders.

Benefits

• Market-benchmarked salaries reviewed annually.
• Meaningful equity.
• Relocation support and visa sponsorship where applicable.
• Flexible working arrangements appropriate to the role and location, with opportunities to collaborate in person.
• Learning and development budgets, including support for training, conferences and growth.
• Comprehensive benefits including health insurance, dental insurance, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships and team socials.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed