# Senior Data Scientist - Company: [Wayve]() - Location: Sunnyvale, California USA - Team: Product & Delivery - Employment type: Full Time - Posted: May 26, 2026 ## Job description ## **The role** 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. 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. 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. ### **Key Responsibilities:** * **ODD Characterization:** + 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. * **Behavioral Competency Mapping:** + 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. * **ODD Permutation & Scaling Framework:** + 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. * **Current model behavioural Pattern Analysis:** + Analyze current model kpi patterns, and common driving behaviors, assess differences in required system behavior and edge case risks. + Collaborate with safety and product on findings and proposals for behavioural improvement. * **Cross-functional Collaboration:** + 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. * **Predictability & MTBF Guidance:** + 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. ## **About you** Essential * 7+ years experience in systems engineering, automotive data analysis, data science, or a related field. * 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 accessing large pools of data from frameworks like DataBricks) 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. Desirable: MS or PhD in Physics, Statistics or Mathematics with specialism in traffic system modeling, autonomous driving deployment, or urban mobility analysis. This role is a full-time role based in Sunnyvale, CA (hybrid) and the reasonably estimated salary for this role ranges from $209,700 to $298,200, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. ## Apply [Apply on Wayve]() Canonical job page: