AI Data Scientist – Expression of Interest

About the role

Bilue is seeking experienced AI Data Scientists to join its talent pool. This is an expression of interest rather than a confirmed vacancy, allowing us to quickly match qualified candidates with upcoming AI projects across our client base.

Key responsibilities

• Design, implement and maintain data catalogues for AI initiatives using platforms such as DataHub, OpenMetadata, Apache Atlas, Collibra or cloud‑native equivalents (AWS Glue Data Catalog, Azure Purview, GCP Dataplex).
• Define metadata schemas and taxonomy standards – including type, version, jurisdiction, validity period and confidence tier – to enable context‑aware retrieval.
• Assess and monitor data quality across client and internal assets with tools like Great Expectations, dbt tests or Soda, flagging stale or ambiguous records before they reach AI models.
• Build and sustain data lineage mappings so AI outputs are fully auditable and traceable to source data.
• Develop automated ingestion pipelines and nightly quality checks to keep catalogues up‑to‑date with minimal manual effort.
• Collaborate closely with AI Engineers to integrate clean, trustworthy knowledge stores into production AI systems.

Required profile

• Strong background in data governance, knowledge management and AI delivery.
• Proven experience designing metadata schemas, taxonomies and data lineage for complex data environments.
• Ability to work independently, partner with engineering teams and communicate technical concepts clearly.

Required skills

• Data cataloguing tools: DataHub, OpenMetadata, Apache Atlas, Collibra, AWS Glue Data Catalog, Azure Purview, GCP Dataplex.
• Data quality frameworks: Great Expectations, dbt, Soda.
• Familiarity with AI/ML pipelines and integration with retrieval systems.