Data Scientist, Robotaxi Performance & Capability

About the role

Before the detail, here's the challenge you'd help us solve.

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.

Here’s what this particular role covers.

🛠️ About our Engineering Teams

How do we know when an AI Driver is ready for a fully driverless Robotaxi service? Our Product Architecture & Safety team brings together data, systems thinking and engineering expertise to help answer that question.

Working closely with Model Development, Behavioural Validation, Safety and Robotaxi Engineering, you’ll turn real-world driving, validation and operational data into evidence of what the Wayve AI Driver can do today—and what needs to improve next. Your work will help shape development priorities and measure progress towards a safe, reliable and scalable driverless service.

🧠 Your day-to-day

You’ll take ownership of hands-on analysis, from exploring complex datasets in Python and SQL to sharing findings that guide product and engineering decisions.

- Investigate driving behaviours and operational events to understand where, why and how often the system falls short of driverless service expectations.

- 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.

- Work with teams across Wayve to turn findings into development priorities, targeted validation and better data collection.

- Contribute to product readiness reviews with clear evidence of progress, remaining limitations and the confidence behind your conclusions.

🧩 What you’ll be working on:

- Understanding driverless readiness: Assess real-world driving and validation data to identify performance gaps, quantify their operational impact and track whether they are closing.

- Separating performance gaps from missing capabilities: Identify where better model performance can help and where additional system or product capabilities are needed.

- Measuring the complete Robotaxi experience: Define metrics for remote assistance, passenger pickup and drop-off, passenger interactions, vehicle readiness and recovery from operational disruptions.

- Evaluating service reliability: Measure intervention demand, mission completion, recovery time and vehicle availability to understand what it takes to deliver a dependable driverless service.

- Exploring challenging scenarios: Investigate safety-critical interventions, unnecessary stops, stuck scenarios and manoeuvre execution across different roads and operating conditions.

🙌 You should apply if:

- You have at least three years of relevant experience in data science, automotive data analysis or a related field, with deeper experience for senior-level opportunities.