# Data Scientist, Data Quality & Provenance **Company**: Wayve **Location**: Leonberg **Work arrangement**: hybrid **Experience**: senior **Job type**: full-time **Category**: Data Science **Industry**: Automotive **Apply**: https://jobs.ashbyhq.com/wayve/4cf45aa3-fccf-4d28-aaaa-0fb0732b8de1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_e7a479ac-351 ## Description We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. About our Data Quality & Provenance Team 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. Your day-to-day - Define measurable, statistically rigorous concepts of data quality, including coverage, label quality, uncertainty, provenance and 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 that clearly communicate confidence, limitations and appropriate interpretation. - Analyse large annotation datasets using Python and SQL to identify quality issues and inform decisions. - Iterate on metrics and reporting based on feedback from the teams using them. What you'll be working on - Statistical methods for distinguishing genuine data-quality problems from label ambiguity, inconsistent annotation or evaluation noise. - Labeler and dataset metrics that support training-data selection, simulation, annotation acceptance and model evaluation. - Reusable quality artefacts that replace one-off analyses with registered, automated metrics and reports. - Multi-rater and human-in-the-loop ML systems, including approaches such as Dawid–Skene-style models, psychometrics and inter-rater agreement. - Quality standards spanning coverage, uncertainty, provenance, annotation quality and predictive-model performance. - Integration of data-science outputs into the platform workflows used by engineering and research teams You should apply if - You have strong foundations in classical statistics, including experimental design, sampling, modelling, estimation and inference. - You have practical experience with rater or annotator modelling, inter-rater agreement, label uncertainty or related methods. - You understand data quality across dimensions such as coverage, label quality, uncertainty, provenance and model performance. - You have worked with annotation tooling, QA methodologies, human-in-the-loop ML systems or multi-rater labelled datasets. - You have strong Python and SQL skills and are confident analysing large, complex datasets. - You can turn ambiguous stakeholder questions into rigorous, usable metrics and clearly communicate uncertainty, limitations and decision implications. - Experience with probabilistic or Bayesian modelling, production platform integrations or safety-critical data would be an advantage. What’s in it for you (Location dependant) - 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 ## Skills ### Required - classical statistics - Python - SQL - data quality - annotation tooling - QA methodologies - human-in-the-loop ML systems - multi-rater labelled datasets ### Nice to have - probabilistic or Bayesian modelling - production platform integrations - safety-critical data --- Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/wayve/4cf45aa3-fccf-4d28-aaaa-0fb0732b8de1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)