Altimetrik
Neo4j Graph Ontology Specialist (Jersey City)
Altimetrik, Jersey City, New Jersey, United States, 07390
Altimetrik delivers outcomes for our clients by rapidly enabling digital business & culture and infuse speed and agility into enterprise technology and connected solutions. We are practitioners of end-to-end business and technology transformation. We tap into an organizations technology, people, and assets to fuel fast, meaningful results for global enterprise customers across financial services, payments, retail, automotive, healthcare, manufacturing, and other industries. Founded in 2012 and with offices across the globe, Altimetrik makes industries, leaders and Fortune 500 companies more agile, empowered and successful.
Altimetrik helps get companies get unstuck. Were a technology company that lives organizations a process and context to solve problems in unconventional ways. Were a catalyst for organizations talent and technology, helping teams push boundaries and challenge traditional approaches. We make delivery more bold, efficient, collaborative and even more enjoyable.
Job Description: Neo4j Graph Ontology Specialist We are seeking a highly skilled Neo4j Graph Ontology Specialist to join our team. This role focuses on building and managing graph-based ontologies to model complex relationships between skills, roles, and individuals. The successful candidate will be responsible for leveraging Neo4j to define, design, and optimize a graph-based ontology structure, facilitating a deeper understanding of skills and roles within our organization or clients. Key Responsibilities: Graph Ontology Modeling : Design and develop an ontology that represents key skills, roles, and people as nodes, with relationships that define how they interact (e.g., HAS_SKILL, REQUIRES_SKILL, WORKS_ON). Cypher Querying : Write and optimize queries in Cypher, Neo4j's query language, to retrieve insights from the graph and identify patterns or relationships. Data Integration : Use Python or other integration tools to ingest data, build the graph structure, and link Neo4j with other systems or platforms. Graph Optimization : Profile Cypher queries to identify performance bottlenecks and optimize them for faster execution. Collaboration : Work with data scientists, software engineers, and domain experts to refine the graph model and ensure its consistency and accuracy. Core Skill Set: Cypher : Expertise in Neo4js native query language, Cypher, is essential for navigating and querying the graph. Graph Data Modeling : Ability to model complex, interconnected data in Neo4j's graph database using node labels (e.g., Person, Skill, JobRole) and relationship types (e.g., HAS_SKILL, REQUIRES_SKILL). Ontology Design : Proven experience in designing and implementing domain-specific ontologies that structure data effectively and maintain consistency across the graph. Query Profiling and Optimization : Proficiency in profiling Cypher queries and optimizing graph performance using tools like PROFILE and EXPLAIN. Python Integration : Strong scripting skills in Python to automate data loading, build graph structures, and integrate with external systems. Advanced and Related Skills: Skill Ontology Engineering : Experience in creating and maintaining dynamic skill ontologies, with an emphasis on representing relationships between skills, roles, and job requirements. Knowledge Graph Construction : Expertise in constructing comprehensive knowledge graphs from raw data, guided by well-defined ontologies. Graph Algorithms : Ability to apply graph algorithms (e.g., shortest path, community detection) to uncover deeper insights and correlations within skill and role data. AI/ML Integration : Experience in leveraging graph-based ontologies to train AI/ML models for applications such as resume screening, job matching, and skills gap analysis. Data Governance & Security : Knowledge of applying ontology reasoning and enforcing security rules within the graph database to ensure compliance and integrity.
Desired Qualifications: Proven experience with Neo4j, including both graph modeling and performance optimization. Familiarity with machine learning algorithms or AI applications in talent management or similar domains is a plus. Strong problem-solving skills with an ability to analyze complex data sets and extract actionable insights. Familiarity with industry standards in data governance, security, and compliance, especially in graph-based databases.
Altimetrik helps get companies get unstuck. Were a technology company that lives organizations a process and context to solve problems in unconventional ways. Were a catalyst for organizations talent and technology, helping teams push boundaries and challenge traditional approaches. We make delivery more bold, efficient, collaborative and even more enjoyable.
Job Description: Neo4j Graph Ontology Specialist We are seeking a highly skilled Neo4j Graph Ontology Specialist to join our team. This role focuses on building and managing graph-based ontologies to model complex relationships between skills, roles, and individuals. The successful candidate will be responsible for leveraging Neo4j to define, design, and optimize a graph-based ontology structure, facilitating a deeper understanding of skills and roles within our organization or clients. Key Responsibilities: Graph Ontology Modeling : Design and develop an ontology that represents key skills, roles, and people as nodes, with relationships that define how they interact (e.g., HAS_SKILL, REQUIRES_SKILL, WORKS_ON). Cypher Querying : Write and optimize queries in Cypher, Neo4j's query language, to retrieve insights from the graph and identify patterns or relationships. Data Integration : Use Python or other integration tools to ingest data, build the graph structure, and link Neo4j with other systems or platforms. Graph Optimization : Profile Cypher queries to identify performance bottlenecks and optimize them for faster execution. Collaboration : Work with data scientists, software engineers, and domain experts to refine the graph model and ensure its consistency and accuracy. Core Skill Set: Cypher : Expertise in Neo4js native query language, Cypher, is essential for navigating and querying the graph. Graph Data Modeling : Ability to model complex, interconnected data in Neo4j's graph database using node labels (e.g., Person, Skill, JobRole) and relationship types (e.g., HAS_SKILL, REQUIRES_SKILL). Ontology Design : Proven experience in designing and implementing domain-specific ontologies that structure data effectively and maintain consistency across the graph. Query Profiling and Optimization : Proficiency in profiling Cypher queries and optimizing graph performance using tools like PROFILE and EXPLAIN. Python Integration : Strong scripting skills in Python to automate data loading, build graph structures, and integrate with external systems. Advanced and Related Skills: Skill Ontology Engineering : Experience in creating and maintaining dynamic skill ontologies, with an emphasis on representing relationships between skills, roles, and job requirements. Knowledge Graph Construction : Expertise in constructing comprehensive knowledge graphs from raw data, guided by well-defined ontologies. Graph Algorithms : Ability to apply graph algorithms (e.g., shortest path, community detection) to uncover deeper insights and correlations within skill and role data. AI/ML Integration : Experience in leveraging graph-based ontologies to train AI/ML models for applications such as resume screening, job matching, and skills gap analysis. Data Governance & Security : Knowledge of applying ontology reasoning and enforcing security rules within the graph database to ensure compliance and integrity.
Desired Qualifications: Proven experience with Neo4j, including both graph modeling and performance optimization. Familiarity with machine learning algorithms or AI applications in talent management or similar domains is a plus. Strong problem-solving skills with an ability to analyze complex data sets and extract actionable insights. Familiarity with industry standards in data governance, security, and compliance, especially in graph-based databases.