Materials Knowledge Architect

Design and own scientific data representations, schemas, and ingestion pipelines that convert heterogeneous external materials data into trustworthy, interoperable, ML-ready datasets. Partner with materials science researchers and external data providers to map formats and standards, resolve quality and provenance issues at the source, and ensure data models support discovery at scale. Build robust ETL-style pipelines for experimental and computed properties, enabling next-generation materials search.