• Own the definition and evaluation of output quality, ensuring consistency and accountability across all internal and external datasets. • Oversee ingestion, cleaning, transformation, and structuring of customer data for AI model training and inference. • Build scalable processes and frameworks for data labeling, annotation tools, quality checks, and feedback loops. • Ensure timely, high quality data delivery for internal R&D and customer deployments. • Own SLAs, accuracy targets, and “definition of quality” for all datasets. • Partner with Product Managers to shape data-related features, workflows, and tooling (e.g., annotation UI, correction UI, model output review tools). • Translate customer needs into clear data requirements and repeatable solutions. • Build and lead a Data Studio team. • Implement best practices for documentation, quality metrics, repeatable workflows, and compliance. • Drive continuous improvements in throughput, cost efficiency, and accuracy. • Work closely with engineering and research teams to define data needs for model training, evaluation, and debugging. • Collaborate with BD team to scope data requirements for onboarding and implementation. • Serve as the subject matter expert on data quality, data formats, labeling standards, and customer specific nuances related to manufacturing design. • Interface with customers to understand their domain, data structures, and quality expectations. • Guide customers through data preparation, schema definition, and ongoing iteration. • Own delivery timelines, reporting, and communication for all active data projects.