Wayve

Wayve

System & Data Scientist

Sunnyvale, California USA · Senior · Full-time

Sponsorship not specified$210k-$298kDetected 103 days ago
PythonSQLDatabricksData AnalysisData EngineeringData ScienceStatisticsSystems EngineeringGISCollaboration

Stay score

odds of building a lasting career here

61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level II · 2×
Level I$125,4861 entry
Level II$168,9172 entries
Level III$212,3263 entries
Level IV$255,7574 entries

$2,626 more$212,326 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.

Based on the DOL prevailing wage for this occupation and worksite, a base salary of $212,326 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Data Scientists" for prevailing-wage purposes.

DOL prevailing wage, 2026-27 wage year · Data Scientists (15-2051) · San Jose-Sunnyvale-Santa Clara, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

12 transfer filings in the last year, covering 12 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About 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.

Responsibilities

  • 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.
  • Recommend minimal data slices needed to support safe and predictable system performance in a new region.
  • Collaborate with safety and product on findings and proposals for behavioural improvement.

Requirements

  • Build and maintain a taxonomy of behavioral competencies (e.g., merging, yielding, unprotected turns, interacting with pedestrians) required to safely operate in each ODD.
  • Analyze current model kpi patterns, and common driving behaviors, assess differences in required system behavior and edge case risks.

Compensation

  • 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.

Benefits

  • 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.
  • Develop a framework to compute and prioritize permutations of ODD parameters and behavioral competencies to optimize data collection, scenario coverage, and scaling efficiency.

Company info

  • 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.

This listing is sourced directly from Wayve's careers page and normalized into a canonical job model.