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Knowledge Graph
hace 2 meses
ABOUT THE OPERATIONS IT TEAM
Operations IT is a global IT capability supporting the Global Operations organisation. We business partner with Operations capability areas: Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics and Global External Sourcing and Procurement. We operate out of Operations hub sites including in the UK, Sweden, US, and China; and out of our Global Technology Centres in India and Mexico.
Here our work has a direct impact on patients – transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining cutting-edge science with leading digital technology platforms and data. All with a passion to impact lives through data, analytics, AI, machine learning and more.
It's a dynamic and challenging environment to work in – but that's why we like it. There are countless opportunities to learn and grow, whether that's exploring new technologies in hackathons, or transforming the roles and work of colleagues, forever. This is your chance to be part of a team that has the backing to innovate, disrupt an industry and change lives.
THIS IS WHAT YOU'LL DO
We are seeking an experienced Knowledge Graph & Semantic Data Engineering Lead to join our Data, Analytics & AI group for Operations IT. This group supports various business areas such as Develop, Manufacture, Supply Chain, Quality and Procurement with data-driven solutions and insights.
As a Knowledge Graph & Semantic Data Engineering Lead, your role is to establish and lead a Knowledge Graph and Semantic capability . You'll develop relationships with the business and start to create a backlog of use cases, in many circumstances you will need to educate the business on the value of semantics and Knowledge graphs.
The ideal candidate possesses a strong background in data analytics, semantics, and knowledge graph technologies with experience in leading semantic and/or knowledge graph teams and able to perform at a strategic level. They should have a background in building and maintaining ontologies and Knowledge graphs.
In this role, you'll contribute to the success of Operations by designing and implementing solutions involving graph and semantic technologies, as well as supporting our AI and Digital deliveries.
Typical accountabilities include:
Strategy
Provide strategy & Vision for Knowledge graph and semantic engineering.
Partner with the AI team to develop a strategy for a Gen AI chatbot to query Operations data products via a knowledge graph.
Guide the development, execution, and implementation of a roadmap for the strategies above.
Collaborate with cross-functional teams and stakeholders to understand business requirements, identify knowledge gaps, and define data-driven strategies to inform decision-making and drive business growth.
Knowledge Graph Platform
Leverage your expertise in graph databases and data engineering to design, develop, and maintain advanced knowledge-based systems and solutions that support our digital initiatives.
Develop and implement advanced data engineering pipelines, including data ingestion, processing, storage, and analysis, ensuring the optimal performance, scalability, and reliability of our data infrastructure.
Apply cutting-edge computer science and data analytics techniques to derive valuable insights from large, complex datasets, and translate these insights into actionable intelligence for our business stakeholders.
Utilize your expertise in Graph DB and Graph query languages to continue developing and maintain existing data models and graph databases, enabling efficient querying and analysis of complex data relationships.
Actively contribute to the continuous improvement of our knowledge engineering processes, tools, and methodologies, fostering a culture of innovation and excellence within the team.
Stay abreast of emerging technologies and industry trends to continuously enhance the organization's Knowledge and semantic capabilities.
Semantic Engineering
You will maintain, evolve, and grow our knowledge models (ontologies), presenting, selling them, and annotating them to provide common understanding.
Collaborate with cross-functional teams to define and document data models using ontological principles.
Conduct ontology mapping and integration to facilitate data interoperability and integration across systems.
Provide training and guidance to stakeholders on ontology usage and best practices for data organization.
Stay updated on industry trends and advancements in ontology development to enhance data management processes.
Stakeholder Collaboration
Collaborate with stakeholders across departments to understand requirements and ensure business needs are met.
Act as a liaison between IT and Business Units, fostering strong communication and understanding.
Oversight of partnerships with multiple third parties, academic or outsourced partners to shape and drive project outcomes and knowledge building.
Deliver business education, improving awareness of KG capabilities, potential use-cases and key benefits within the wider business.
Quality Assurance
Implement and oversee robust quality assurance processes to ensure the accuracy, reliability, and security of data.
Establish and monitor key performance indicators to measure the effectiveness of Knowledge Graph services.
YOU WILL NEED TO HAVE
Experience in leading a similar capability with the ability to interact with senior business stakeholders.
Knowledge Graph and Semantic Analysis: You'll need multi-disciplinary capabilities to explain, design, and create powerful knowledge graph models. Balancing business and technical understanding is crucial to the role.
Excellent Communication Skills: Be an effective, passionate, trusted advocate and communicator for Graph and Semantic Technologies.
Use Case Awareness: Be aware of the breadth of use cases for these technologies. Prudent user interface design that exploits the power of graphs while mitigating visualization challenges.
Focused on Gen AI: Designing, developing, and deploying customised and scalable knowledge graph solutions or products with emphasis on graph data modelling, graph traversal, graph theory and graph analytics or graph AI.
Thinking Skills: Excellent problem-solving, analytical, and critical thinking skills, with a keen attention to detail.
Data and Information Architecture: Understand data and information architecture, along with the modelling languages.
Knowledge Representation and Semantic Technologies: Sound understanding of semantic modelling (OWL, RDF, etc.), data integration, knowledge graph design.
Experience with knowledge graph technologies: Familiarity with triple stores, Neo4j, taxonomy management tools.
Query Languages: Deep practical knowledge of Cypher, SPARQL, or any other major GQL.
Other Databases: Working knowledge of a range of database technologies, relational and NoSQL.
WHY JOIN US
Here our work has a direct impact on patients – transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining cutting-edge science with leading digital technology platforms and data.
Join us at a crucial stage of our journey in becoming a digital and data-led enterprise. Make the impossible possible by building partnerships and ecosystems, creating new ways of working and driving scale and speed to deliver exponential growth.
SO, WHAT NEXT?
If you're interested in applying, we encourage you to apply using your completed Workday profile where possible.
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