Data Scientist, Robotaxi Performance & Capability

Wayve • Sunnyvale, CA

10d • Hybrid

About The Position

The Data Scientist will work within Wayve’s Product Architecture & Safety team to help determine 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 capability and areas for improvement. The analysis will inform development priorities and 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 developing metrics, performance baselines and dashboards across model, software and product releases. The Data Scientist will apply statistical methods to assess rare events, quantify uncertainty and distinguish meaningful changes from noise. They will collaborate across Wayve to guide development priorities, targeted validation and data collection, and contribute evidence-based product readiness reviews that explain progress, limitations and confidence in conclusions.

The position also covers assessing driverless readiness and performance gaps; distinguishing gaps addressable through model improvements from missing system or product capabilities; defining metrics across the Robotaxi experience; measuring service reliability; and investigating challenging driving scenarios and operational conditions. The role is available hybrid in Sunnyvale or remotely within the USA.

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 proficiency 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 analysing complex systems, identifying 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 approaches as new evidence emerges.
• Clear communication skills with engineering, product and leadership stakeholders, including the ability to explain findings and their limitations.

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 with a focus on traffic systems, autonomous driving deployment or urban mobility.

Responsibilities

• Explore complex driving, validation and operational datasets using Python and SQL.
• Investigate driving behaviours and operational events to understand where, why and how often the system falls short of driverless service expectations.
• Assess real-world driving and validation data to identify performance gaps, quantify operational impact and track whether gaps are closing.
• Identify whether performance issues can be addressed through better model performance or require additional system or product capabilities.
• Build practical metrics, performance baselines and dashboards to track progress across model, software and product releases.
• 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 evaluate service reliability.
• Investigate safety-critical interventions, unnecessary stops, stuck scenarios and manoeuvre execution across roads and operating conditions.
• Apply statistical methods to assess rare events, quantify uncertainty and distinguish meaningful improvements from noise.
• Work with teams across Wayve to turn findings into development priorities, targeted validation and improved data collection.
• Contribute clear, evidence-based product readiness reviews describing progress, limitations and confidence in conclusions.

Benefits

• Salaries benchmarked against the market annually.
• Meaningful equity.
• Relocation support and visa sponsorship where applicable.
• Flexible working arrangements appropriate to the role and location.
• Learning and development budgets, with support 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.

What This Job Offers

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