At IMO Health, Semantic Data Modelers are key members of our ontology-driven graph engineering team, helping to build and maintain a virtualized, intelligent, and scalable medical terminology platform. Your work will empower over 740,000 clinicians by enhancing how healthcare data is structured, delivered, and understood.
We are seeking a highly experienced and strategic Senior Semantic Data Modeler to join our team, with a specialized focus on Knowledge Graphs. In this critical role, you will lead the design, development, and governance of complex semantic models that empower both human and machine understanding of our most vital clinical concepts and terminology relationships. You will serve as a key resource, bridging the gap between diverse raw data sources and strategic business needs by crafting a robust, consistent, and highly accessible knowledge layer. This position requires exceptional collaboration skills, working closely with our staff semantic engineers, clinicians, and content teams, a keen eye for defining intricate data structures, and a commitment to ensuring the highest data quality and accessibility for semantic enrichment and clinical interoperability initiatives.
Compensation at IMO Health is determined by job level, role requirements, and each candidate’s experience, skills, and location. The listed base pay represents the target for new hires with individual compensation varying accordingly. These figures exclude potential bonuses, equity, or sales incentives, which may also be part of the total compensation package. Our recruiter will provide additional details during the hiring process.
IMO Health also offers a comprehensive benefits package. To learn more, please visit IMO Health’s Careers Page.
WHAT YOU'LL DO:
Semantic Model Development: Drive the end-to-end design, development, and evolution of complex semantic data models, with a primary focus on ontologies, knowledge graphs, and property graphs.
Strategically Translate Business Requirements: Transform intricate, cross-functional business needs into formal, scalable knowledge graph structures, ensuring tight alignment with the enterprise data strategy and long-term architectural vision.
Define, Document, and Govern Semantic Assets:Establish best practices for, and create comprehensive documentation of, semantic models, including detailed entity definitions, relationship types, axioms, constraints, and data lineage, fostering clarity, consistency, and reusability across the organization.
Cross-Functional Collaboration: Partner closely with staff semantic engineers, clinicians, content teams, and business leaders to deeply understand their domain knowledge and requirements, translate complex concepts into actionable models, and ensure that semantic solutions effectively meet organizational objectives.
Implement Robust Data Quality & Consistency: Design and implement data quality frameworks, validation rules, and transformation logic within the semantic layer to ensure the accuracy, reliability, and consistency of the knowledge graph.
Optimize and Scale Knowledge Graph Performance: Drive the optimization of knowledge graph structures, query performance, and usability for diverse data consumption scenarios, including advanced analytics, AI applications, and self-service initiatives.
Innovate and Set Standards: Continuously research, evaluate, and recommend new technologies, methodologies, and best practices in semantic modeling, knowledge graph technologies, ontology engineering, and cloud-based analytics to drive continuous improvement.
Mentor and Guide: Provide leadership and mentorship to junior data modelers and engineers, fostering a culture of knowledge sharing and excellence in semantic modeling practices.
WHAT YOU'LL NEED:
BA/BS in a STEM field with 7+ years of hands-on work experience with a significant portion dedicated to semantic modeling and knowledge graph development, including experience in a lead or senior capacity.
Deep and demonstrated expertise in designing, building, and managing ontologies, knowledge graphs, and property graphs.
Extensive experience with leading graph database platforms (e.g., Amazon Neptune) and advanced proficiency in graph query languages (e.g., SPARQL).
Strong working knowledge of OWL, RDFS, SHACL, and other semantic web standards.
Experience with enterprise data modeling tools (e.g., Erwin) and specialized ontology/graph modeling tools
Strong understanding and hands-on experience with relational databases (SQL) and familiarity with NoSQL databases (e.g., PostgreSQL).
Proven ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders, and to lead collaborative efforts across diverse teams.
Demonstrated ability to analyze complex data challenges, identify root causes, and architect strategic, scalable solutions within a semantic context.
Practical experience with AWS services related to data and ELT methodologies is often preferred.
Experience in an Agile/Scrum environment, iteratively developing and deploying data solutions.
Bonus: Understanding of healthcare ontologies and standards like SNOMED-CT, LOINC, RxNorm, and ICD-10.
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