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For Companies At a Glance
- Tasks: Design and maintain ontologies for data integration and AI applications.
- Company: Join a forward-thinking company focused on innovative AI solutions.
- Benefits: Enjoy remote work flexibility and opportunities for professional growth.
- Why this job: Be part of a cutting-edge team shaping the future of AI and knowledge engineering.
- Qualifications: Strong background in ontologies and graph databases is essential.
- Other info: Initial 6-month contract with potential for extension.
The predicted salary is between 48000 - 72000 £ per year.
Job Description
Role = Ontology Consultant
Duration = Initial 6-month contract
Location = UK (Remote)
Job Spec
Key Responsibilities
- Ontology Development and Knowledge Engineering
- Design, build, and maintain ontologies to support data integration and semantic reasoning.
- Leverage ontologies to enhance data pipelines and enable advanced knowledge engineering solutions.
- Collaborate with AI teams to ensure ontology structures efficiently support Agentic AI applications, including RAG pipelines and Agent Orchestration.
- Graph Database Expertise
- Work with both Semantic Graph and Property Graph technologies, understanding their unique architectures and use cases.
- Utilize Semantic Graph tools for rule-based inference and semantic reasoning.
- Employ Property Graph tools like Neo4j, Amazon Neptune, and TigerGraph for network analytics and data exploration.
- Integrate graph solutions with AI and machine learning systems, ensuring seamless knowledge retrieval and reasoning.
- Network Science Application
- Apply network science techniques to analyze and interpret complex relationships within graph data.
- Develop algorithms and models to extract insights from graph structures and relationships.
- Use network insights to enhance AI systems’ ability to reason across interconnected data sets.
Skills
Required Skills and Qualifications
- Strong expertise in ontologies, including their design, implementation, and application in real-world scenarios.
- Proficiency in graph database technologies, with hands-on experience in both Semantic Graph and Property Graph systems.
- Solid understanding of network science concepts and their practical applications in graph engineering.
- Familiarity with standards such as RDF and W3C for Semantic Graphs, as well as bespoke standards for Property Graphs.
- Ability to mentor and train junior team members, fostering a culture of learning and growth.
- Experience integrating AI considerations (like LLM-based retrieval, RAG pipelines, and Agent Orchestration) into graph ecosystem design.
Preferred Qualifications
- Experience with data pipelines and integrating graph databases into larger data ecosystems.
- Knowledge of rule-based inference systems and network analytics tools.
- Strong problem-solving skills and the ability to work independently on complex technical challenges.
- Prior exposure to enterprise AI initiatives, demonstrating an understanding of how knowledge graphs support agent-based architectures.
Ontology Consultant employer: Russell Tobin
Contact Detail:
Russell Tobin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Ontology Consultant
✨Tip Number 1
Familiarise yourself with the latest trends in ontology development and knowledge engineering. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of graph databases and ontology consulting. Attend relevant webinars, workshops, or meetups to build connections and gain insights that could give you an edge in your application.
✨Tip Number 3
Showcase your hands-on experience with Semantic Graph and Property Graph technologies. If you have worked on projects involving Neo4j or similar tools, be prepared to discuss these experiences in detail during interviews.
✨Tip Number 4
Prepare to demonstrate your understanding of network science concepts and their applications. Think of examples where you've applied these techniques to solve complex problems, as this will highlight your practical knowledge and problem-solving skills.
We think you need these skills to ace Ontology Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your expertise in ontologies and graph database technologies. Include specific examples of projects where you've designed or implemented ontologies, and mention any relevant tools you've used.
Craft a Compelling Cover Letter: In your cover letter, express your passion for ontology development and knowledge engineering. Discuss how your skills align with the job requirements, particularly your experience with Semantic Graph and Property Graph technologies.
Showcase Relevant Experience: When detailing your work experience, focus on roles that involved network science applications and AI integration. Use metrics to demonstrate your impact, such as improvements in data retrieval or efficiency in data pipelines.
Highlight Mentorship Skills: Since the role involves mentoring junior team members, include any previous experience you have in training or leading teams. This will show your ability to foster a collaborative environment and contribute to team growth.
How to prepare for a job interview at Russell Tobin
✨Showcase Your Ontology Expertise
Be prepared to discuss your experience with ontology design and implementation. Highlight specific projects where you've successfully built ontologies that enhanced data integration or supported AI applications.
✨Demonstrate Graph Database Knowledge
Familiarise yourself with both Semantic Graph and Property Graph technologies. Be ready to explain their architectures and use cases, and share examples of how you've used tools like Neo4j or Amazon Neptune in past projects.
✨Discuss Network Science Applications
Prepare to talk about how you've applied network science techniques in your work. Share insights on algorithms or models you've developed to analyse complex relationships within graph data.
✨Emphasise Mentorship and Collaboration
Since mentoring junior team members is part of the role, think of examples where you've trained others or fostered a collaborative environment. This will show your ability to contribute to team growth and knowledge sharing.
