Job Description:
- Work experience with healthcare ontologies and biomedical vocabularies (SNOWMED, ICD, HCPCS, RxNorm, DrOn, UMLS, etc.)Deep understanding of Property and Knowledge graphs, and differen
- Pragmatic understanding of limitations and benefits related to using public ontologies, building custom ontologies, and purchasing commercial ontologies.
- Familiarity with ontology engineering practices and modelling trade-offs. Working knowledge of ontology modelling tools (Protégé, Top Braid, etc.)Hands-on experience
- implementing and consuming OWL / RDFS / Turtle / SHACL. Familiarity in dealing with data conformity and ETL workflows in Graph ingestion
- Working understanding of the relationship AI/Client pipelining and development integration. This will enable the adoption and innovative use of Graph in the enterprise.
- Familiarity with utilization of rules engines and understanding of inference materialization in practice.
- Software engineering background in object oriented design principles and development such as Java/Scala/Python.
- Identify and implement solutions to meet business objectives and support emerging priorities. Work with Knowledge Solutions and Technology teams to develop solutions and test system functionality to ensure new products, enhancements, bug fixes and patches have correctly identified problems without introducing regression issues.
- Lead initial phases of the data migration planning effort.
- Work with business partners to implement and integrate systems and enhancements. Identify change management requirements; assist in the development of training materials and documentation.
- Proven knowledge and experience with Graph development, and testing methodologies as they relate to the business areas being supported.
- Success leading technical graph efforts and teams with medium to large business initiatives.
- Able to work independently with minimal direction and guidance from project lead and manager.
- Strong data process analysis and problem solving skills.
- Affinity for technical writing and presenting – ability to formally document requirements, reach agreements with others, and explain detailed requirements to others as needed.
- Hands-on experience with graph database and the desire to work in a high performing and faced-paced team.
- Hands on experience with the design, development, testing, and deployment of graph database solutions.
- Design and develop graph data models in accordance with leading practices for Evernorth use cases.
- Work with system owners and data engineers to identify and integrate with data sources used to hydrate the knowledge graph
- Create and manage queries to pull insights from the knowledge graph.
- Optimize for high performance, efficiency, scalability, and stability of the database.
- Define the database architecture and development best practices.
Formal Education and/or Training:
- More than 5 years’ technical lead skills
- Strong ability to lead and work with others on cross-team projects
- Familiarity of graph and relational database concepts
- Fluency with graph query languages such as Gremlin, Cypher, SPARQL.
Preferred Qualifications:
- Strong educational background in healthcare analytical discipline.
- Greater than 5 years’ relevant information systems graph and RDBMS related experienceDemonstrated ability to lead program-level business analysis database projects, feasibility studies, competitive analysis and business cases; ability to mentor, coach and train business analysts.
- Demonstrated problem solving skills and the ability to work collaboratively with other departments to resolve issues. Experience with system development methodologies.
- Strong track record of delivery using Neo4j graph databases.
- Excellent communication skills including the ability to communicate effectively in both formal and informal contexts in a fashion tailored for the audience.
- Ability to work in a fast-paced environment, handling multiple priorities; communicate with individuals at all levels of an organization.
- Comments for Suppliers: The Consultant, Health Care Knowledge Graph platform (Neo4j)
- Work experience with healthcare ontologies and biomedical vocabularies (SNOWMED, ICD, HCPCS, RxNorm, DrOn, UMLS, etc.).
- Deep understanding of Property and Knowledge graphs, and differences
- Pragmatic understanding of limitations and benefits related to using public ontologies, building custom ontologies, and purchasing commercial ontologies
- .Familiarity with ontology engineering practices and modelling trade-offs. Working knowledge of ontology modelling tools (Protégé, Top Braid, etc.)
- Hands-on experience implementing and consuming OWL / RDFS / Turtle / SHACL. Familiarity in
Source: Indeed.com
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