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
As a Data Scientist supporting AI Engineers, you will partner with one or more engineering teams to develop actionable insights that guide improvements to the Wayve AI Driver. Through experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety and performance of the Wayve AI Driver.

This is a full-time role based in our London office, with two days a week in the office as part of our hybrid working model.

Your day-to-day

You will work closely with engineering and cross-functional partners to turn data into clear, practical direction. Your findings will help teams understand performance, validate product requirements and prioritise the opportunities that matter most.

You will be comfortable working asynchronously across time zones, communicating findings clearly and compellingly, and influencing team direction through evidence.

What you'll be working on:

• Formulating and iterating on the performance metrics that organise our engineering efforts and guide progress towards commercial success.
• Designing experiments and targeted off-road measurements to help ensure we deliver customer product requirements while maintaining safety and performance.
• Investigating factors in model training and inference that create bottlenecks in functionality and performance.
• Identifying, testing and validating hypotheses that can unlock improvements to the Wayve AI Driver.
• Summarising, visualising and communicating findings in an accessible way that supports prioritisation and strategy.

You should apply if:

• You have 3+ years of experience in a Data Science role.
• You are fluent in querying and building large datasets, including writing production-level SQL for data-transformation pipelines.
• You have experience designing robust real-world experiments, such as A/B tests, and critically evaluating test statistics.
• You have strong statistical foundations, including selecting appropriate distributions and testing the assumptions behind frequentist statistics.
• You are proficient in a statistical scripting language and data science or machine-learning packages, such as Python with pandas, sklearn, statsmodels or scipy, or R with dplyr, caret or stats.
• You are skilled at summarising, visualising and communicating findings in an accessible and compelling way.
• You have influenced team direction through your findings and bring a bias towards actionable insight that can drive prioritisation and strategy.
• You are comfortable working asynchronously across time zones with cross-functional partners.
• You are deeply curious about building something new and excited by the opportunity to help define AV2.0 and how we build it.

It would be great if you also have:

• Practical machine-learning experience, for example with PyTorch, and a passion for taking research ideas to production.
• A track record of promoting statistical rigour and experimental best practices.
• Experience with causal inference, econometric techniques or Bayesian methodologies for hypothesis testing.
• Experience working with large datasets and distributed computing technologies, such as Spark, Hadoop or other map-reduce tools.
• Experience working in a fast-moving technology company or startup.

Not ticking every box? That's totally okay! If you're passionate about autonomy and keen to learn, we encourage you to apply even if you don't meet every requirement.

How we work - Locations & Flexible Working:

Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.

The Interview Process:

Our process is clear and respectful of your time:

• Initial call / recruiter screen (30 mins)
• Competency interviews (Hiring Manager interview and SQL or Python programming interview) 45/60 min
• Deep-dive technical interviews (Quant Domain interview and Causal Inference Case Study) 60 min each
• Final leadership interview (30 mins)

We'll always explain the format and work around your availability.

What's in it for you:

Salaries benchmarked against the market annually
Meaningful equity, sharing in the ownership and long-term success of Wayve
Relocation support and visa sponsorship where applicable
• Hybrid working, core hours and the chance to work hands-on in vehicle workshops and labs
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, team socials and more.

A quick, honest note before you apply.

Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you'll help write it. That suits people who want real ownership more than people who need a settled structure from day one.

If that sounds like the kind of problem you want to spend your time on, we'd really like to hear from you.