Data Analyst, Wayve
2-5 days a week in office (Sunnyvale, CA)
Autonomous mobility driven by AI
Job no longer available
Autonomous mobility driven by AI
201-500 employees
Job no longer available
2-5 days a week in office (Sunnyvale, CA)
201-500 employees
Company mission
To reimagine autonomous mobility through embodied intelligence.
Role
Who you are
- We are looking for a highly analytical and systems-minded ODD & Behavioral Competency Analyst to lead the analysis of Operational Design Domains (ODDs), traffic patterns, and regulatory behaviors across our target markets
- Strong background in systems engineering, transportation analysis, data science, or a related field
- Proven experience with traffic system modeling, autonomous driving deployment, or urban mobility analysis
- Experience analyzing or defining ODDs in the context of AV/ADAS technologies is a strong plus
- Familiarity with traffic regulations and human driving behaviors across multiple geographies
- Proficiency in data analysis tools (e.g., Python, SQL, GIS, Jupyter) and ability to visualize ODD and scenario coverage metrics
- Ability to work cross-functionally and translate domain analysis into technical and product requirements
- Experience working in an agile, fast-scaling environment with a strong execution mindset
What the job involves
- As part of our mission to scale end-to-end embodied AI for autonomous driving, we are building a world-class Data Management team focused on unlocking high-quality, targeted data acquisition that drives model performance and predictability
- This role will be critical in defining what data is needed, where, and how much, in order to build models with high Mean Time Between Failures (MTBF) and generalization capabilities across varied geographies
- Analyze and define the operational design domain (ODD) for each target market or region, including geography, infrastructure, weather, road types, traffic density, and local driving behaviors
- Identify ODD boundaries, edge conditions, and failure triggers to inform data collection and system design
- Build and maintain a taxonomy of behavioral competencies (e.g., merging, yielding, unprotected turns, interacting with pedestrians) required to safely operate in each ODD
- Quantify the complexity and frequency of each competency based on local traffic data, regulations, and real-world observations
- Develop a framework to compute and prioritize permutations of ODD parameters and behavioral competencies to optimize data collection, scenario coverage, and scaling efficiency
- Recommend minimal data slices needed to support safe and predictable system performance in a new region
- Analyze traffic laws, enforcement patterns, and common driving behaviors in new markets to assess differences in required system behavior and edge case risks
- Collaborate with legal and safety teams to map regulations to system-level behavioral expectations
- Work closely with data engineering, safety, simulation, product, and deployment teams to turn ODD and competency insights into actionable data strategies and deployment plans
- Provide input to scenario library development, synthetic data generation, and test case prioritization
- Use historical data and statistical models to identify data gaps or high-variance behaviors that impact MTBF performance
- Provide guidance on what additional data is needed to reach MTBF targets in each ODD segment
Our take
Wayve is developing artificial intelligence (AI) that teaches cars to drive autonomously using reinforcement learning, simulation, and computer vision. Wayve’s core premise is that the big breakthrough in self-driving cars will come from better AI brains rather than more sensors or “hand-coded” rules which it believes are highly restrictive and not at all scalable.
The company said that it trains its autonomous driving system using simulated environments and then transfers that knowledge into the real world, where it emulates how humans adapt to conditions in real time. It ultimately relies on end-to-end deep learning AI rather than hard-engineered AI. This is one of the world's hardest problems to solve, but Wayve has made an exciting start and is taking a very different approach to competitors like Uber and Waymo, who are relying more on sensors.
Following a few years of innovative breakthroughs, Wayve now has backing from high-profile investors such as Microsoft and angels, including Uber's chief scientist Zoubin Ghahramani and Pieter Abbeel, a UC Berkeley robotics professor and pioneer of deep reinforcement learning. The company's strategic partnerships with outfits like Asda and Ocado to test-run autonomous deliveries, as well as publicity through the Minister is a show of confidence in the future of Wayve's solution to autonomous driving.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 7 rounds)
May 2024
$1.1bn
SERIES C
Jan 2022
$200m
SERIES B
Total funding: $1.3bn
Company benefits
- Learning budget
- In-house chef
- Flexible Working
- Private health insurance and therapy
- Workplace nursery scheme
- Onsite bar
- Large social budgets
- Enhanced parental leave
Company HQ
London, UK
Leadership
Alex Kendall
(CEO)Has a PhD from Cambridge in Computer Vision & Robotics. Previously Research Engineer at Skydio and Advisor to Scape Technologies
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