Data Scientist, Data Quality & Provenance Team

Job summary

Responsibilities

Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.

• 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.

Tech stack

• Python
• SQL