Senior Data Quality & Provenance Scientist (AI Platform)

wayve • Germany

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AI Summary

Lead the development of statistically rigorous data quality frameworks for Wayve’s autonomous driving AI systems. Design metrics, tools, and automated reporting to ensure trustworthy data, annotation, and model evaluation. Collaborate cross-functionally to integrate data science outputs into platform workflows for engineering and research teams.

Key Highlights

Develop statistically robust methods for data quality, annotation, and model evaluation in autonomous driving AI systems.

Design metrics, tools, and automated reporting to ensure data trustworthiness across coverage, label quality, and uncertainty.

Collaborate with annotation, autonomy, and evaluation teams to translate quality challenges into defensible, actionable metrics.

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Key Responsibilities

Define measurable, statistically rigorous concepts of data quality (coverage, label quality, uncertainty, provenance, model performance).

Apply statistical inference methods to multi-rater annotation, label ambiguity, dataset coverage, and black-box model evaluation.

Partner with annotation, autonomy, and evaluation teams to translate practical quality questions into defensible metrics.

Build automated reports to communicate confidence, limitations, and appropriate interpretation of data quality signals.

Analyze large annotation datasets using Python and SQL to identify quality issues and inform decisions.

Iterate on metrics and reporting based on feedback from engineering and research teams.

Technical Skills Required

Statistics (experimental design, sampling, modeling, inference) Python SQL

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Benefits & Perks

Market-benchmarked annual salaries

Meaningful equity

Relocation support and visa sponsorship where applicable

Hybrid working with core hours

Comprehensive benefits (health insurance, dental, enhanced parental leave, retirement, wellbeing partnerships)

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Nice to Have

Experience with probabilistic or Bayesian modeling

Production platform integrations

Safety-critical data experience

Dawid–Skene-style models or psychometrics

Multi-rater or human-in-the-loop ML systems

Job Description

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.Our Data Quality & Provenance team sits within Wayve’s AI Platform organisation and builds the evidence that helps teams make confident decisions about the data underpinning our embodied AI systems. We develop statistically robust methods, metrics and tools to determine when data-quality, annotation and evaluation signals can be trusted—and when they cannot.

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