Ontologist and Knowledge Graph Specialist

About Growthsphere:

We are a leading entity in Investment Technology, leveraging cutting-edge technology to enhance decision-making and operational efficiency. We are currently seeking a highly skilled Knowledge Engineer with expertise in ontology and knowledge graph construction to join our dynamic team.

Introduction:

We are seeking a highly skilled and dedicated Knowledge Engineer to join our team. This role focuses on the development and integration of ontologies and the construction of knowledge graphs to enhance data understanding and usage across our systems. The ideal candidate will be instrumental in driving our efforts to leverage structured knowledge domains, enabling advanced data analytics and machine learning applications.

Key Responsibilities:

• Design and implement ontologies for various knowledge domains, especially finance, ensuring interoperability and scalability.
• Develop and maintain large-scale knowledge graphs, integrating disparate data sources into a cohesive and queryable structure.
• Utilize Python for scripting and automation tasks related to data handling and knowledge graph operations.
• Collaborate with data scientists and analysts to define data needs, gather requirements, and deliver structured data models that support organizational goals.
• Train machine learning models and fine-tune large language models (LLMs) for specific tasks, optimizing performance and accuracy.
• Contribute to the development of internal tools and frameworks that support the extraction, transformation, and loading (ETL) processes for knowledge graph construction.
• Ensure data quality and integrity within knowledge graphs by implementing robust testing and validation processes.
• Stay updated with the latest industry trends, tools, and technologies in knowledge engineering, ontology, and artificial intelligence.
• Participate in workshops, seminars, and other events to enhance professional skills and organizational knowledge.

Requirements:

• Master’s degree in Computer Science, Information Science, Artificial Intelligence, or a related field.
• Profound knowledge of Python programming, with experience in data manipulation and automation.
• Solid experience in ontology development and semantic web technologies (e.g., RDF, OWL, SPARQL).
• Demonstrable expertise in designing and building large-scale knowledge graphs.
• Experience in machine learning, with practical knowledge of training models and fine-tuning large language models.
• Strong analytical and problem-solving skills, coupled with excellent communication and collaboration abilities.
• Familiarity with database management, data governance, and data integration techniques.
• Proven ability to work independently and manage multiple projects in a dynamic and fast-paced environment.

Preferred Qualifications:

• Experience with graph databases like Neo4j, Amazon Neptune, or similar.
• Publication or contribution to research in related fields.
• Experience with cloud services (AWS, Azure, Google Cloud) and their data services ecosystems.