Associate Scientist, Data II

Responsibilities:

• Graph data modeling. Contribute to Design and refine labeled-property and/or RDF graph models — nodes, relationships, properties, and constraints — that accurately represent entities and their connections across source systems.
• Pipeline development. Build, test, and maintain ingestion pipelines that extract data from relational, document, and file-based sources, transform it, and load it into the graph using batch and incremental patterns.
• Query engineering. Write, optimize, and document Cypher queries for data loading, validation, entity resolution, and downstream retrieval, including support for graph-backed and retrieval-augmented applications.
• Data quality and validation. Implement constraints, validation rules, entity resolution (e.g., SHACL or property checks), and automated tests that keep the graph consistent, traceable, and trustworthy.
• Performance and operations. Monitor graph performance, tune indexes and queries, and assist with environment management across development, validation, and production tiers.
• Collaboration and documentation. Partner with cross functional teams, analysts, and domain subject-matter experts to gather requirements; document data models, lineage, and design decisions clearly for technical and non-technical audiences.
• Required:
• Bachelor’s Degree with 2 years’ experience; or Master’s Degree equivalent education with no additional experience.
• Exposure with software development life cycle including Git, testing, and basic CI/CD workflows.
• Exposure with at least one graph database (e.g., Neo4j, Amazon Neptune, Tiger Graph, or an RDF triple store) and its query language (Cypher or SPARQL).
• Exposure with any data analysis programming languages (e.g., SQL, Python & Apache Spark, SAS & R) including structured and unstructured data.
• Preferred:
• Exposure working with entity resolution, record linkage, knowledge graph construction, vector databases and embeddings, and retrieval-augmented generation (RAG) or graph-RAG patterns is preferred.
• Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: