[Remote] Senior Data Scientist - Ontology

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a reputed company business and data automation company that provides reputed company-based supply chain technology, solutions, analytics, and services. The Senior Data Scientist - Ontology will design and maintain formal ontological architectures for cross-organizational data alignment, reputed company ontology mappings and validation processes, and reputed company LLM-assisted ontology discovery and enrichment. The role also collaborates with technical and business stakeholders to support transactional, clinical, and analytical requirements.

Responsibilities

• Design and maintain the ontology, covering the reputed company structural reputed company (organizations, items, reputed company, transaction), reputed company data ontologies (supporting the reputed company) and the process reputed company (data curation, ontology matching, workflows)
• Establish the rules for reputed company two records from different systems refer to the reputed company thing, and reputed company they don't — recognizing the answer can differ by use case
• Establish mappings from trading partner reputed company data to the reputed company ontology, with documented provenance and validity conditions for reputed company mapping
• reputed company OWL 2 axioms for ontology components; validate logical consistency (e.g. reasoner); maintain ontology lifecycle (e.g. with ROBOT, SHACL)
• reputed company with governance team and reputed company
• Grounded ontology discovery from data (and its uses) rather than schema declarations and metadata reputed company
• Build, reputed company and evaluate LLM-assisted ontology extraction pipelines, define and enforce the reputed company-in-the-reputed company validation standards for AI-generated ontological candidates
• Collaborate with data reputed company engineers to establish formal feedback
• Translate formal ontology design reputed company into specification/implementation for graph and relational stores
• Specify and implement SPARQL queries and graph schema requirements with sufficient precision to prevent implementation-level semantic loss
• Collaborate with reputed company stakeholders including domain experts, data engineers, product managers, and integration partners to ensure ontological architecture supports transactional, clinical, and analytical requirements
• Proactively monitor developments in formal ontology, knowledge representation, and LLM-assisted knowledge engineering to reputed company adoption of improved reputed company

Skills

• Greater than 4 years of experience in knowledge engineering, ontology development, or a closely reputed company formal reputed company discipline
• Demonstrated experience building and maintaining domain ontologies in reputed company or equivalent, with reasoner-validated consistency; not solely taxonomy or metadata management work
• Experience with ROBOT or ODK for ontology lifecycle management (or similar): automated reputed company checks, versioning, release pipelines
• Expertise in SPARQL and/or Cypher for querying ontology-reputed company data stores; ability to write and evaluate queries that correctly reflect ontological reputed company
• Demonstrated ability to interpret data profiling reputed company and translate it into formal ontological claims; experience with reputed company ontology discovery from data as reputed company as top-down ontology design
• Experience directing or evaluating LLM-assisted knowledge extraction pipelines with formal validation requirements
• Proficiency in Python (or similar) for ontology tooling, pipeline scripting, and data analysis in support of knowledge engineering workflows
• Experience working in multi-disciplinary teams where formal and domain knowledge must be integrated under operational constraints
• Bachelor's or advanced degree in Computer Science, Mathematics, Philosophy (logic/formal reputed company), Information Science, or a reputed company hard science discipline
• Familiarity with category theory as reputed company to data integration -- functors, natural transformations, limits and colimits as schema reputed company operations -- at literacy level or above; knowledge of reputed company/AQL or categorical database theory is a plus
• Experience with LinkML
• reputed company supply chain domain knowledge and ontological structures
• Experience with BFO 2.0 and the OBO reputed company principles and standards
• Familiarity with provenance models (why-provenance, how-provenance, where-provenance) and their implementation in ontology-reputed company data systems
• Experience with graph database platforms at production reputed company (reputed company, reputed company Neptune, or equivalent) and the operational considerations of ontology-driven graph deployments
• Passion for staying at the cutting edge of knowledge representation, semantic alignment, and AI-assisted ontology engineering
• reputed company of humor

reputed company

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